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Fuel Cell Hybrid Drive Train

Master Thesis in Energy Engineering

January 2010

Patryk Kinn

Supervisors: Joachim Lindström Azra Selimovic Lars Bäckström

Examinatior: Robert Eklund


AbstractThis thesis presents a fuel cell hybrid drive train study of a 26 ton distribution truck regarding the fuel consumption. The investigation is made using a model implemented in Simulink. The concept vehicle is a Volvo FM9, where the conventional diesel power train is replaced by an electrical drive system. The electrical propulsion motor is powered by a proton exchange membrane fuel cell assisted by a Li-ion power optimised battery. The power ratings of the investigated fuel cells are between 150 kW and 350 kW and the investigated battery capacities range from 4.5 kWh to 22.6 kWh. Two drive cycles, where one represents urban distribution with no road incline and the other represents suburban distribution including road incline are used. By implementing three different power control strategies, it is shown that the fuel consumption can be reduced by up to 56 % compared to the conventional diesel reference vehicle. The urban distribution drive cycle is found more suitable for the fuel cell vehicle application. A 250 kW fuel cell and 13.6 kWh battery configuration is suggested for the urban distribution drive cycle, reducing the fuel consumption by 53 %. For the suburban distribution drive cycle the suggested configuration consists of a 350 kW fuel cell and a 17.8 kWh battery, reducing the fuel consumption by 25 %.


AcknowledgementsThere are several people that I would like to mention and thank explicitly for their contributions during this thesis work. These people are:

Joachim Jindström who supervised me and contributed greatly by his knowledge and experience within the field of electric machines. I am grateful for his warm, experienced and open minded guidance during the entire working process and support during the finalisation of the report.

Azra Selimovic, for answering that very phone call during her time abroad that led to the work on this thesis and for initiating this project. I appreciate her advice during my work.

Andreas Bodén, who together whit Azra initiated this project and handled it over to the experienced guidance of Joachim.

Paul Adams who contributed with expertise on issues regarding hydrogen storage and the English language.

Jens Groot who provided the battery model and patiently answered all my questions.

Mikael Holber, for companionship and interesting conversations about fuel cell technology, martial arts and argentine tango.

The entire group 6120 for the warm welcoming I received, for continuously answering my questions and for generously providing a broad spectrum of expertise.


Nomenclature

A Front Area of the vehicleAf Tafel equation constanta Vehicle accelerationafc Fuel cell stack area Cd Drag coefficientCr Rolling frictionEV Electrical Vehicle

Faraday constantFCV Fuel Cell VehicleFd Drag forceFIwheel Force due to moment of inertia of the wheelsFmgx Force due to gravityFroll Force due to rolling resistance Ftot Sum of the external forcesFtr Traction forceg Acceleration of gravitygf Gibbs free energyH2 Total hydrogen consumptionHEV Hybrid Electric VehicleICE Internal Combustion EngineI-SAM Integrated Starter Alternator MotorIwheel Moment of inertia of the wheelsImotor Moment of inertia of the motori Current densityio Exchange current densityK Specific heat ratioLHVdiesel Lower heating value of dieselLHVH2 Lower heating value of hydrogenlfactor Length factorM Vehicle MassMH2 Molar mass of hydrogenMair Molar mass of airm Mass transport constant mn Mass transport constant nncell Number of cells P1 Compressor inlet pressureP2 Compressor outlet pressurePcomp Compressor power Pfc,in Power entering the fuel cellPfc,out Power delivered by the fuel cellPm Motor powerPm,max Maximum motor power Pwheel Wheel powerPo Ambient pressurePH2 Partial pressures of hydrogenPH2O Partial pressures of water vapour

Saturation pressure of water


PO2 Partial pressures of oxygenR Gas constantr Wheel radiusrf Area-specific resistanceSOC State of charge T TemperatureTwheel Wheel torqueTm Motor torqueTm,max Maximum motor torqueTin Inlet temperatureTmodel,max Maximum original output torque Voc Open circuit voltage

oocV Open circuit voltage at standard pressure and temperature

v Vehicle speedvbase Vehicle speed corresponding to motor base speedvmax Maximum vehicle speedxgear Gear ratioΔSOC Delta stare of chargeΔVohm Ohmic resistance lossesΔVact Activation lossesΔVmass Mass transportation lossesηfc,system Fuel cell system efficiency ηdcdc DC/DC converter efficiencyηis Isentropic efficiencyηel Electric efficiencyηtot Total mechanical derive line efficiency Incline angle

2H Molar flow of hydrogenair Molar flow of air

ρair Air densityρdiesel Diesel densityωm Motor speedωm,motor Maximum motor speedωmax,wheel Maximum wheel speedωwheel Wheel speed

wheel

Wheel acceleration

Table of contentIntroduction.................................................................................................................................1

The fuel cell vehicle................................................................................................................1Prerequisites................................................................................................................................3

Purpose and goal.....................................................................................................................3Concept vehicle.......................................................................................................................3Data and performance specification........................................................................................4Drive cycles............................................................................................................................4

Sizing..........................................................................................................................................5Performance............................................................................................................................7Drive cycle............................................................................................................................10

The model and components......................................................................................................11The driver..............................................................................................................................11The fuel cell system..............................................................................................................11

The fuel tank.....................................................................................................................12The fuel cell......................................................................................................................13The compressor.................................................................................................................16

The auxiliary load.................................................................................................................17The electric motor.................................................................................................................17The final gear........................................................................................................................19The vehicle body...................................................................................................................19The battery............................................................................................................................20The controller........................................................................................................................20

Control strategy.........................................................................................................................20Power demand.......................................................................................................................21

Simulations...............................................................................................................................21Battery and fuel cell sizes.....................................................................................................21Delta SOC correction............................................................................................................22Performance and fuel consumption......................................................................................22

Results.......................................................................................................................................24Performance..........................................................................................................................24Fuel consumption..................................................................................................................33

Discussion.................................................................................................................................43Performance..........................................................................................................................43Fuel consumption..................................................................................................................43General..................................................................................................................................45

Conclusions...............................................................................................................................46Future work...............................................................................................................................47References.................................................................................................................................48


IntroductionThe emission and fuel consumption favourable operation of the Hybrid Electric Vehicles (HEVs) have resulted in tremendous popularity increase of these vehicles during the last two decays [1]. The electric vehicle is however not a new concept and the manufacturing of such vehicles started as early as before 1900. Ferdinand Porsche’s first hybrid vehicle produced in 1899 was for instance propelled by four wheel-mounted electric motors with a series driveline solution [1].

The lack of insight in the finite nature and in the environmental impact of the fossil fuels, as well as the fast development of the internal combustion engine (ICE) during the Firs Word War and the low fuel prices, pushed the electric vehicles aside [2]. Since then, the ICE vehicles have dominated the roads and have now probably done that far longer than any of those driving them today can remember. The infrastructure, performance demands, manufacturing process and many other aspects have been influenced and formed by this dominance. Now however, when the environmental impact of the traffic caused pollution is becoming visible and the fossil fuel reserve of this planet fades rapidly, new possibilities to developed alternative powertrain concepts arise. This development may even be considered as necessary if the freedom of using fast and flexible personal and goods transports are not to be abandoned meanwhile the planets environment is preserved for the future generations.

A substantial amount of research and development time, as well as financial means is now invested by the manufacturers and political organs in order to meet the demands from a constantly more aware public. Even if large advance has already been made, there are still many aspects to be considered and problems to be solved regarding the HEVs before they can be fully commercialized. Two such aspects are the cost and performance of these vehicles. Because even if the environmental concern has been brought to attention, the customers must be able to afford the product and the product needs to fulfil its purpose. Another aspect is the origin of a substitution fuel and its distribution. Various research and development activities have resulted in a variety of different hybrid solutions, from the electric motor assisted bicycles to more advanced plug in hybrid cars and the fuel cell vehicles (FCV). This theses aims to contribute to a general effort of HEV study by investigating the fuel consumption of a fuel cell based drive line solution for a 26 tonne distribution truck.

The fuel cell vehicleWhen there are at least two forms of energy stored on board a vehicle that can be used for propulsion and if the energy in at least one of the cases is electric, such a vehicle qualifies to be called a HEV. Since this is the case for the FCV, where the propulsion energy can be taken from the hydrogen supplied to the fuel cell or from the electric energy stored in the battery, these vehicles can be regarded as HEVs.

The drive line of the HEV is usually one of three basic types. One type is the series drive line imposing that only one energy form is used to power the propulsion. The other two types are the parallel and complex drive line solutions [2]. The parallel drive line impose that two energy forms can be used at the same time and the complex driveline impose that both the series and parallel drivelines are implemented and that a choice is made which solution to use in a certain situation. All these drive line solutions have their pros and cons when compared to one another. However, since the energy used to power the propulsion motor of the FCV is electric, the series drive line solution is only one studied in the following work.

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Since the FCV is propelled by electric energy, this type of vehicle posses the same potential of emission favourable transportation as the battery sourced electric vehicle (EV). The fuel cell however, gives the benefit of extended travelled distance for the same or even smaller battery size. This reduction in battery dependence is desirable since the battery, at present, can be regarded as the Achilles heel in all hybrids [3] due to e.g. low life time and high cost. The fuel cell technology however introduces other challenging aspects. One issue is the absence of fuel distribution infrastructure, making it hard to commercialize the fuel cell vehicle. To deal with this problem there are several demonstration projects of hydrogen highways around the world and ongoing research on storage possibilities. In a sense this issue is partially addressed in this thesis, where the fuel consumption and storage capacity is investigated.

Naturally it has to be kept in mind that for this emission favourable concept to become reality, the hydrogen needs to be produced and distributed in equally emission favourable way. In the ideal case also the manufacturing process, service and the recycling process all need to be emission favourable. Even if these issues are of great importance and strongly related to the environmental benefits of the FCV and other types HEVs, they are not considered in this text and left for other inspired investigators and future studies.

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PrerequisitesIn this section the purpose and the goal of the theses are presented. The concept vehicle, the performance requirements and the drive cycles chosen are also presented. The first subsection deal whit the purpose and goal and is followed by a motivation of the vehicle selection. The following subsections introduce the vehicle data, the performance requirements and the drive cycles chosen for the fuel consumption simulations.

Purpose and goalThe purpose of this thesis is to conduct a pre study on a hydrogen based fuel cell series hybrid drive train for a medium-heavy distribution truck. The focus of the study is to simulate and evaluate different system layouts for the drive train and define pros and cons for each concept defined regarding mainly the fuel economy. The basic case will be an equivalent conventional diesel driven vehicle. Other important parts of the work are to define and scale the components of the system such as hydrogen storage, battery, electric machine and fuel cell. Important aspects here are to define the power balance between the fuel cell, electric machine and the battery.

The goal with this thesis is to deliver a model taking most of the important aspects of the drive train into account. The model level should be accurate enough to deliver reliable results for basic vehicle analysis. The results are compared with those of a conventional drive train as well as state of the art diesel-electric parallel hybrid drive train.

Concept vehicleThe vehicle chosen for this study is the Volvo FM 9 illustrated in Figure 1. The vehicle choice is primary motivated by two factors. The first factor is the large amount of reference material and vehicle data specified in the report on the I-SAM project [4]. The reference material includes fuel consumption of the conventional version of this vehicle.

The second factor motivating the choice of the vehicle is the possibility of using the Volvo FM 9 for city delivery applications, which was the initial proposal of the theses. During the literature study in the initial part of the project it was however discovered that a similar investigation has already been performed for a light distribution truck [5]. Being nearly twice as heavy as the vehicle already investigated (FL6), the Volvo FM9 was chosen in order to contribute to the results of the existing investigation.

Figure 1: The Volvo FM [6].

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Data and performance specificationThe physical data of the vehicle are summarized in Table 1.

Table 1: The Volvo FM9 dataWeight (loaded) 26 ton Rolling friction, Cr 0.005 N/NFront area, A 9.7 m2

Drag coefficient, Cd 0.65Wheel radius, r 0.492 mAuxiliary load 4.4 kW

The following performance requirements have been chosen for the study:

1. Cruising ability: The vehicle shall be able to cruise at 100 km/h at level ground.2. Grade ability: The vehicle shall be able to cruise at 40 km/h at the incline of

8.7 % (5o).3. Acceleration: The vehicle shall be able to perform maximal acceleration from

stand still to 100 km/h at level ground.The vehicle shall be able to perform maximal acceleration from standstill to 50 km/h at the incline of 8.7 % (5o).

As will be shown later on, the grade ability requirement is demanding. For comparison it can be stated that the highway E6, when passing the Hallandsåsen in Sweden in the southern direction, has the incline of 6% (3.43o).

Drive cyclesTwo different drive cycles have been selected for the study. The sort3 drive cycle and the sx365 drive cycle. The sort3 drive cycle is a synthetic cycle with a completely flat road topology during the entire duration. It consists of an acceleration section, a constant velocity section, a deceleration section and a stand still section repeated for three different constant velocities. The constant velocities are 30 km/h, 50 km/h and 60 km/h. During one simulation this drive cycle is driven ten times. The sort3 drive cycle is considered suitable for city distribution [4].

The sx365 drive cycle correspond to an actual road in the neighbourhood of Hällerd test ground in Sweden, it is hilly and contains few stops. The sx365 drive cycle is considered suitable for suburban distribution [4]. Data summery for both drive cycles is presented in Table 2. The reference speed of the sort3 cycle is shown in Figure 2 and the corresponding speed of the sx365 cycle is illustrated in Figure 3, where the road topology has been included. The fuel consumption of the reference truck and the I-SAM truck are given in Table 3.

Table 2: Drive cycle data summary [4].sx365 sort3

Duration [s] 2150 200Distance [m] 35660 1450Stop time [%] 7 % 20 %Average speed [km/h] 60 26Average speed excluded stops [km/h] 65 49Maximal speed [km/h] 90 60Route topology yes no

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Table3: Fuel consumption of the reference vehicle [4].Drive cycle Reference truck I-SAM truck

sort3 5.68 [l/10 km] 4.66 [l/10 km]sx365 4.29 [l/10 km] 4.08 [l/10 km]

Figure 2: Speed profile of the sort3 drive cycle. Figure 3: Speed and height profile of the sx365 drive cycle

Apart from the fact that fuel consumption of the reference vehicle for these two drive cycles is documented, the choice of sort3 cycle is motivated by the city delivery suitability while the choice of sx365 cycle is motivated by the hilly road topology and suburban driving representation.

SizingThe information about the drive cycles includes velocity and acceleration requirements as well as the slope of the driveway during the entire cycle. This information, and the performance requirement information stated in the previous section, combined with the vehicle data and Newton’s second low of motion can be used for an estimation of the electric motor requirement and the gear ratio.

Traction forceThe first step in this sizing process is the computation of the traction force that is required at the wheels for propulsion of the vehicle. As postulated by Newton in his second low of motion, the motion of the vehicle will depend on the resulting force from all external forces acting on the vehicle. These external forces are the traction force , the rolling resistance force , the drag force and the gravitational force [7]. When the vehicle is accelerating there are also additional forces due to the moment of inertia. One such force, the force corresponding to the moment of inertia of the wheels, is included in the following calculations. The corresponding force due to the moment of inertia of the motor, shafts and transmission are omitted in the sizing calculations for simplicity, but are included in the actual simulation model.

The rolling resistance force, the drag force, the gravitational force and the forces due to the moment of inertia of the wheels are calculated according to:

(1)

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(2)

(3)

(4)

Where M is the vehicle mass, g is the acceleration of gravity, is the density of air, v is the vehicle speed, is the incline angle, is the moment of inertia of the wheels and is the angular acceleration of the wheels. The sum of the external forces, the force is:

(5).

According to Newton’s second low, following expression resulting in the traction force can be stated, where is the acceleration of the vehicle:

(6).

Traction powerThe wheel power that is required for propulsion or that is regenerated during braking can be calculated from equation (6) using the following expression:

(7)

(8).

Wheel torqueThe torque that needs to be delivered to the wheels for propulsion or that is received during braking can be calculated from the traction force equation (6) using the following expression:

(9)

(10).

Gear ratioThe wheel torque and speed are related to the motor torque and speed by the gear ratio. The gear ratio can be calculated assuming a maximal motor speed, a maximal speed of the vehicle

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and deciding the number of gear steps. In the calculations below it has been assumed that the maximal speed of the motor is 8000 rpm (837.76 rad/s), corresponding to an existing model of the traction motor. The maximal speed of the vehicle has been chosen to 28 m/s, corresponding to approximately 100 km/h. The reduction gearbox consists of one fixed gear. The expression for the gear ratio can be written:

(11)

where is the maximal rotational speed of the motor and is the maximal rotational speed of the wheels. The rotational speed of the wheels is computed by converting the corresponding vehicle speed according to:

(12).

Using the values stated above yields a gear ratio 14.72.

Motor torqueThe power is apart from the efficiency, equal to the power of the electric motor. Since the power can be calculated as the product of toque and rotational speed, the wheel torque is related to the motor torque by the gear ratio assuming a lossless transmission:

(13)

(14).

In equation (13) is the rotational speed of the motor. The existing model of the motor is scaled to meet the desired torque-speed characteristics by the use of a length factor, as explained in the traction motor section. A suitable torque characteristic is selected in the next section.

PerformanceThis section is devoted to acceleration requirement calculations. For comparison, the power and torque demand at the wheels for the cruising ability and grade ability requirements are summarized in table 4. These values are calculated using equation (8) and (10).

Table 4: The power and torque demand at the wheels.Requirement Maximum Power [W] Maximum Torque [Nm]

100 km/h & zero incline 122701 2173

40 km/h & 5 degree incline 266755 11812

Based on experience within Volvo Technology [8] a wheel torque of approximately 20 000 Nm is requested to fulfil the performance requirements. An electric machine having a maximum output torque of 1385 Nm is therefore chosen as a first assumption. Using a total mechanical derive line efficiency of 0.97 and the gear ratio calculated earlier, this machine

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delivers a maximum torque of 19400 Nm and a maximum power of 373.5 kW to the wheels. Also, now that the performance of the motor is determined, the motor inertia can be included in the calculations.

Circumscribing equation (6) regarding the traction force, taking into account the motor inertia and expressing the wheel toque in terms of motor torque the following expression for the acceleration can be written:

(15)

(16).

The motor torque in equation (18) is a function of the motor speed according to the characteristic shown in Figure 13. Expressing the motor speed in terms of the vehicle speed according to:

(17)

and using the power and torque characteristic of the electric motor, the equation for the vehicle acceleration becomes:

for (18)

for (19)

for (20)

The nominal speed used above, is the vehicle speed corresponding to the base speed of the motor. Solving the differential equation using the assumed motor characteristics and for a road incline of 8.7 % results in the speed profile shown in Figure 4. The corresponding profile for level road is shown in Figure 5. As can be seen, the assumed motor is sufficient for the acceleration requirement.

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Figure 4: Speed profile during at 8.7 % incline.

Figure 5: Speed profile at level road.

Drive cycleUsing equations (8) and (10), and the information about the drive cycle, it is possible to calculate the power and torque demand at the wheels during the drive cycle in question. The maximum power and torque demands calculated are presented in Table 5.

Table 5: The power and torque demand at the wheels.Drive cycle Propulsion Power

[W]Propulsion Torque

[Nm]Brake Power

[W]Brake Torque

[Nm]sort 3 310021 14576 319780 9996

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sx365 475687 23649 1167203 25972

The sx365 drive cycle is the most challenging cycle of the two selected. The maximal power and torque demands at the wheels are larger than the corresponding maximum values of the electric motor. These are however peak values delivered intermittently. As shown in figure 6, the selected characteristics of the electric motor will only cause minor deviation from the reference speed. Figure 6 shows the seeped profile during the sx365 drive cycle obtained using the selected motor, powered by a 150 kW fuel cell and a 15.8 kWh battery. Sizing the electric machine to recuperate all of the braking energy will result in an oversized machine. It is assumed that the mechanical brake will be able to handle the brake demand if the electric motor is insufficient.

Figure 6: The vehicle speed and the drive cycle reference speed

The model and componentsThe top level of the Simulink model consists of two blocks, representing the driver and the vehicle respectively. This level is shown in Figure 7 and the structure of the vehicle representation block is shown in Figure 8. The driver model and the components of the vehicle representation are described in this section.

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Figure 7: The top level of the model.

Figure 8: The content of the vehicle block.

The driver The driver is modelled as a PI-controller having the proportional constant of 1 and the integration constant of 0.25 [9]. The speed set point is the reference speed of the drive cycle and the speed error is calculated using the actual speed of the vehicle. The output signal is an acceleration or brace pedal signal.

The fuel cell systemThe fuel cell system consists of a hydrogen tank, a fuel cell stack, an air compressor, and a dc/dc converter. The dc/dc converter is used to transform the fuel cell voltage to the system voltage. In the converter model ideal voltage conversion is assumed and a constant efficiency of 95 % is used to model the power loss. The modelled fuel cell is of the proton exchange membrane type. According to Yjyanti et al. [10] the DOE target price and weight of a corresponding system is 45 $/kW and 650 W/kg respectively. These figures are however based on high-volume manufactured cost of a 80 kW net output power system and not necessarily representative for how cost will scale whit power.

The fuel tankThe hydrogen storage tank is assumed to be lossless and to deliver the hydrogen at the required pressure to the fuel cell. In the tank model, the hydrogen consumption is calculated by integrating the hydrogen molar flow over time. The mass of consumed hydrogen presented in the result section is calculated using the molar mass of hydrogen having the value of

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2.016 kg/kmol [11] and the computation of diesel equivalent is made according to the following equation:

(21).

where is the total hydrogen consumption in moles, and are the lower heating values of hydrogen and diesel respectively, 120000 kJ/kg and 42800 kJ/kg, and is the density of the diesel fuel having the value of 0.845 kg/l [11].

The mean consumption per 10 kilometres presented in the result section, is calculated using the total fuel consumption and the total distance travelled. This mean consumption includes the fuel consumed during standstill.

The largest diesel tank available for the reference vehicle is 2030 mm long. This tank has the volume of 810 l and the diesel storage capacity is 97 % of the tank volume. Using the fuel consumption of the sort3 drive cycle presented in table 3, the distance possible to travel with the reference vehicle without refilling is 1383 km. The corresponding operation range using the sx365 fuel consumption is 1832 km. For comparison it can be mentioned that the travel distance between Stockholm and Gothenburg in Sweden is approximately 500 km.

When storing the hydrogen on board the vehicle, tubular cylinders of carbon fibres whit a 350 mm internal diameter and hemi-spherical ends can bee used. If the hydrogen is stored at a pressure of 70 MPa, which is reasonable due to the emerging industry standard and safety issue, the external diameter of these tanks can be assumed to be 450 mm. Another emerging industry standard is 35 MPa and the external diameter for this application can be assumed to be 400 mm [12]. At the pressure of 70 MPa and the temperature of 288.15 K hydrogen has the density of 40.18 g/l. For the same temperature and the pressure of 35 MPa the density of hydrogen is 24.01 g/l [13]. Assuming the tubular cylinders have the same external length as the original fuel tank, the hydrogen storage capacity of one tube is 7009.93 g at 70 MPa and 4304.36 g at 35 MPa. The hydrogen storage data are summarised in table 6. Using these storage capacities, the number of tubes required to mach the travel range of the reference vehicle can be computed.

Table 6: Hydrogen tank data.Pressure [MPa]

Length [mm]

Internal diameter

[mm]

External diameter

[mm]

Internal volume

[l]

External volume

[l]

Hydrogen density

[g/l]

Hydrogen capacity

[g]35 2030 350 400 179.23 238.34 24.01 4304.3670 2030 350 450 174.46 299 40.18 7009.93

The fuel cellThe open circuit voltage calculation is based on the Nernst equation having the following form [14]:

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(22)

where is the open circuit voltage at standard pressure and temperature , is the molar gas constant, is the Faraday constant, , and are partial pressures of hydrogen, oxygen and water vapour respectively and is the saturation pressure of water at the temperature . The open circuit voltage at standard pressure is calculated according to:

(23),

where is the Gibbs free energy of formation for the fuel cell reaction

at the temperature of 80oC having the value of -228.2 kJ/mol [14].

The operational voltage is calculated by subtracting from the open circuit voltage of equation (22) the losses associated with operational conditions. These losses are the ohmic losses due to electric and ohmic resistance, the activation losses associated with driving the chemical reaction and the mass transportation losses caused by the changes in concentration of the reactants and products. The losses are calculated according to:

(24)

(25)

(26)

where is the current density. The values of the constants used in the calculations are summarized in table 7 [14]. Using the equations above the operational voltage can be calculated according to:

(27)

(28)

(29).

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Using the form of equation (29) it is possible to adapt the operational voltage calculation to the results of experimental measurements on a specific fuel cell. In this study literature data are used, since such experiments are not performed. Figure 9 shows the cell voltage as a function of current for the fuel cell used in the model.

Figure 9: The cell voltage as a function of current for the fuel cell model used.

Table 7: Constants used in the operation voltage calculations [11][14].Quantity Abbreviation Value

Gibbs free energy gf 22.8 kJ/molFaraday constant F 96485.3 C/molGas constant R 8.32 J/molKTemperature T 353.15 KPartial pressures of hydrogen PH2 300 kPaPartial pressures of oxygen PO2 62.84 kPaAmbient pressure Po 100 kPaSaturation pressure of water PH2O 71.124 kPaPartial pressures of water vapour Po

H2O 47.416 kPaTafel equation constant Af 0.03 VExchange current density io 0.04 mA/cm2

Area-specific resistance rf 245 nΩcm2

Mass transport constant m m 21.1 µVMass transport constant n n 0.008 cm2/mA

The power delivered by the fuel cell is calculated using:

(30)

where is the number of cells connected in series and is the fuel cell stack area. The power density for one cell is illustrated in Figure 10 where it can be seen that the power drops rapidly if the current exceeds a certain value. This drop is related to the operational

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voltage characteristics of the fuel cell shown in Figure 9. In the model, the maximum hydrogen flow is therefore limited to the maximum power operation point. This limitation impose a strict increase in delivered power when the flow is increased a strict decrease in delivered power when the flow is decreased.

Figure 10: Cell power density as a function of current.

Since the current is the result of electrons transferred during the fuel cell reaction it is possible to write the following relation between the current density and the hydrogen flow :

(31).

The fuel cell system efficiency is calculated according to:

(32),

where is the power consumed by the compressor, is the dc/dc converter efficiency and is the power entering the fuel cell with the hydrogen flow. The power entering the fuel cell is calculated using the lower heating value and the molar flow of hydrogen according to:

(33).The fuel cell system efficiency is used in the control strategies variations described in the controller section. The efficiency of a 250 kW fuel cell system is shown in Figure 11.

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Figure 11: Fuel cell system efficiency for a 250 kW system.

The fuel cell model receives a power demand from the controller. By using a lookup table based on equations (30) and (31) the hydrogen flow required to deliver this power demand is computed. A lower and an upper limit for the hydrogen flow are introduced. The upper limit corresponds to the maximum power operation point and the lower limit depends on the control strategy. The hydrogen flow is used to calculate the corresponding air flow demand and these two flow demands are sent to the controller. The controller increases the air demand by 50 %1 and sends a signal to the hydrogen tank and the air compressor to deliver the corresponding flow to the fuel cell. The hydrogen flow and the air flow entering stack model are used to compute the amount of hydrogen that can react in the fuel cell reaction. This commutation assumes 50 % excess air. The power delivered by the fuel cell is calculated from the stack voltage and current, corresponding to the hydrogen that has reacted.

The compressorThe electrical power requirement to compress a gas from the inlet pressure of to the outlet pressure can be calculated using [10]:

(34)

where and are the molar flow and molar mass of air respectively, and are the isentropic and electric efficiencies respectively, is the inlet temperature and is the specific heat ratio. The constant values in equation (34) are summarized in Table 8 and the isentropic efficiency is illustrated in Figure 12. The isentropic efficiency of the compressor is calculated using a look up table based on data used in other hybrid projects at Volvo Technology [5]. The pressures and correspond to the ambient and cathode pressures respectively.

Table 8: Constants values used in the compressor power calculation.P1 100 kPa

1 For this study the air stoichometry of 1.5 and dead end operation of the fuel cell is chosen.

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P2 300 kPamair 0.02897 kg/molCp 1005 J/kgKηel 0.95Tin 293.15 KK 1.4

Figure 12: Isentropic efficiency of the compressor as a function of the airflow Q.

The auxiliary loadThe auxiliary load is modelled as a constant power demand of 4.4 kW, se Table 1. This power corresponds to the auxiliary load of the reference vehicle and is assumed to cover all ordinary auxiliary loads such as steering servo, suspension, lightning, instruments, wipers etc. It is assumed that the mechanical losses of the reference truck, due to belt or gear transmission, correspond to the losses of the electrical to mechanical energy transformation in the fuel cell application.

The electric motorThe electric motor model is based on a model used in other hybrid projects at Volvo Technology [5] that is scaled by the use of a length factor to deliver the required output torque. The length factor is calculated using the maximum required output torque and the maximum output torque that the original motor is capable of delivering according to:

(35).

The base and maximum speeds of the motor are 248 rad/s and 834 rad/s respectively. These values are the original values and are not changed by the use of the length factor. The maximum power of the scaled motor is 385 kW and the maximum torque is 1385 Nm. The envelope of the scaled motor is illustrated in Figure 13.

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Figure 13: The speed and torque characteristics of the electric motor.

The losses related to the electric motor are calculated using a lookup table based on the motor torque and speed. Beside the losses in the electric motor itself there are additional losses due to the inverter used to convert the dc-buss voltage of the dc side to the ac voltage of the motor. These converter losses are included in the motor losses. The efficiency of the electrical drive system is illustrated in Figure 14.

Figure 14: Motor efficiency as a function of torque and speed.

In the model of the electric motor the actual angular speed and the actual battery voltage are used to find the maximum available torque. This torque is multiplied by the acceleration or brake signal ([-1…1]) from the driver to calculate the torque that is to be delivered to the transmission. A look up table is used to find the associated losses and the electrical power necessary to deliver this torque is computed. This power is added to the power delivered by the fuel cell system and the resulting power value is supplied to or from the battery. If the resulting power value is positive then the fuel cell power is insufficient and power is drawn

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from the battery. If the resulting power value is negative there is excess power and the excess is stored in the battery. The delivered motor torque is sent to the final gear block where it is converted to wheel torque.

The final gearA gear box of one fixed gear step is used in order to take advantage of the possibility offered by the electric motor drive to implement smother driving conditions and reduce the gearbox size and losses. The efficiency of the final gear is assumed to be 0.97 [5]. The gear ratio used is calculated in the sizing section.

The model of the final gear include, beside the final gear itself, also the rare axel modelled with an efficiency of 0.97. The inertia and angular velocity of the motor is multiplied by the gear ratio and the driving axel inertia is introduced. The calculated torque and inertia values are sent to the vehicle body block.

The vehicle bodyIn the vehicle body model, the forces described in the sizing section are represented. The retarding torques acting on the wheels are subtracted from the torque delivered to the wheels by the propulsion system. The acceleration is calculated from the resulting torque by the use of vehicle mass and the inertia of the motor, the drive axel and the wheels. This computation is in a sense the same as the one shown in equation (15). The difference is the torque representation instead of using force. The computed acceleration is integrated resulting in the speed that is sent to the driver block. The distance travelled is calculated in a second integration step.

The batteryThe battery model corresponds to a Li-ion power optimized battery, developed for hybrid vehicles. The model was presented by Jens Groot at Volvo Technology [15] and the only changes made are to the interface that has been adapted to the rest of the model. In the model a monitoring function is implemented making sure that the current and the state of charge (SOC) stays within values that do not harm the battery. If this values are exceeded the battery model stops the simulation. The different battery sizes used in the simulations are modelled by altering the number of battery strings connected in parallel. The weight and capacity of the simulated battery string configurations are presented in Table 9. The nominal power of the battery is 60 kW and 45 kW per string for charge and discharge respectively [15]. According to a forecast presented by the Green Car Congress [16], the prices of Li-ion batteries will in 2010 be 940 $/kWh and fall to 470 $/kWh in 2015.

Tabele 9: The weight and capacity of the battery string configurations.Strings 2 3 4 5 6 7 8 9 10

Capacity [Wh] 4500 6800 9100 11300 13608 15800 18100 20400 22600

Weight [kg] 83 124 165 206 248 289 330 372 413

The controller The controller unit receives signals about the road topology, the acceleration demand and the brake demand. These signals are sent to relevant vehicle units. The control unit is also the unit that computes the power demand that is to be requested from the fuel cell and communicates

19


the flow requests of the stack model to the hydrogen tank and compressor models. The power computation performed depends on the chosen control strategy.

Control strategyThe control strategy is a set of rules dictating how the energy onboard the vehicle is to be managed and a set of threshold values telling when each rule is too be applied. The choice of this strategy is crucial for the vehicle performance [1].

Several control strategies have been tested by previous investigators [17]. Based on a literature study, as well as consultations whiten Volvo Technology, a load following strategy has been selected. The load following strategy is a strategy where the power demand sent to the fuel sell follows the net load at each time. The SOC deviation from a certain reference value is taken into the calculation in this model. The reference value has been chosen to 0.5 and the computation of the corresponding power demand is made by scaling the deviation by a constant. The variation of power demand that the fuel cell system can not handle dynamically is supplied by the battery.

The load following strategy is further complemented by one of three conditions. The first condition states that the minimum power demand sent to the fuel cell is the power corresponding to minimum fuel cell system efficiency of 20 %. The second condition allows the power demand to drop to zero, at low demand resulting in a negative net power from the fuel cell system. This negative power is a result of the low compressor efficiency at the corresponding low air flows. The third alternative control strategy shuts down the fuel cell if the fuel cell system efficiency drops below 20 % under the condition that the battery SOC is greater than 50 %. These three control strategies are in the following text called a, b and c respectively and are summarized in table 10 below.

Tabel 10: Control strategiesStrategy a Minimal fuel cell system efficiency of 20 %Strategy b Any fuel cell system efficiency allowed and a minimal fuel cell power of 0 W allowedStrategy c The fuel cell disconnected if the fuel cell system efficiency is below 20 % and SOC is 50 % or more

Power demandThe computation of the fuel cell power demand is illustrated in Figure 15. The power demand of the electric motor, the compressor and the auxiliary loads are added up whit the power corresponding to the SOC deviation from the reference value. The power is filtered using a time constant of 20 s to eliminate the fast transients and a limit for how fast the power can change is introduced. This limit states that the fuel cell power can change from zero to maximum power in 3 seconds and this rate is linear through the power spectra of the fuel cell. A final limit is introduced to make sure that the power does not exceed the maximum or minimum fuel cell power and the resulting power demand is sent to the fuel cell stack.

20


Figurer 15: Fuel cell power demand computation performed by the control unit.

SimulationsThis section starts whit a description of the battery and fuel cell sizing process and a presentation of the chosen configurations. The ΔSOC correction used in the fuel consumption calculations is presented and the preference simulations and fuel consumption simulations are explained thereafter.

Battery and fuel cell sizesFuel cells of five different maximum power outputs, as shown in Table 11 and 12, were chosen to be investigated. In order to find appropriate battery sizes, simulations of the drive cycles where performed and the following two conditions checked:

1. The battery model is not to end the simulation, which happens when the current or SOC reach a critical value.

2. The SOC value is to be kept approximately between 0.3 and 0.6, some deviation is allowed.

The conditions are chosen with respect to the battery lifetime and health [18]. The upper limit for the battery size is set to 22.6 kWh (413 kg) in order to keep the weight of the battery system within reasonable values.

The resulting configurations for the sort3 and sx365 drive cycles are presented in Table 11 and 12 respectively. Two configurations satisfying condition one but not condition two above, i.e. the simulation is not ended by the battery monitoring function but the SOC variation is be on the chosen values, have been included in the simulations of the sx365 drive cycle. These configurations are represented by red stares and are included to make the graphical representation homogenous. These two configurations are possible to use but are not to be recommended due to the lifetime shortening stress the battery is subjected to.

Table 11: Battery and fuel cell configurations tested on the sort3 driving cycle. Fuel Cell

[kW]Strings:

2Strings:

3Strings:

4Strings:

5Strings:

6Strings:

7Strings:

8Strings:

9Strings:

10150 X X X X X X X X X

21


200 X X X X X X X X X250 X X X X X X X X X300 X X X X X X X X X350 X X X X X X X X X

Table 12: Battery and fuel cell configurations tested on the sx365 driving cycle. Fuel Cell

[kW]Strings:

5Strings:

6Strings:

7Strings:

8Strings:

9Strings:

10150 * * X X X X200 X X X X X X250 X X X X X X300 X X X X X X350 X X X X X X

Delta SOC correctionIf the SOC of the battery at the end of the simulation differs from the value at the beginning of the simulation, this difference will influence on the fuel consumption. The net charging of the battery is either caused by excess operation of the fuel cell and hence increased fuel consumption or by a discharge of the battery and hence reduced fuel consumption. As shown by R. Smokers [19], the introduced deviation can be compensated by a ΔSOC correction. In the ΔSOC correction method, every simulation that is to be performed is repeated for different initial SOC values and the fuel consumption is plotted as a function of the ΔSOC. The consumption for the case of zero ΔSOC is estimated by interpolation. In the correction performed in this thesis three initial SOC values have been used. The values are 40 %, 50 % and 60 %, and the fuel consumption presented in the result section is the interpolated value.

Performance and fuel consumptionDuring the fuel consumption simulations as well as the performance simulations the vehicle weight of 26 tons is used, corresponding to a loaded vehicle. When checking the two requirements of constant speed, i.e. the cruise ability and the grade ability requirements, the vehicle is allowed to gradually accelerate to the reference speed under zero incline during the first 60 seconds of the simulation. The incline is then changed to the incline in question while the reference speed is unchanged. The control strategy activated during this simulation is strategy a. The fuel cell and battery configurations simulated and presented in the results section are chosen regarding the relevance in order to limit the number of simulations and excessive output data. For the sake of comparison, grade ability simulations for the incline of 6 % and 5.5 % are included. The maximum acceleration requirements are simulated using an additional block in the driver routine. During the simulation this block instructs the driver routine to request maximum acceleration at all time until the target velocity is reached. This is achieved by forcing the set value of the PI controller to the orders of 100 times higher than the actual reference speed and stopping the simulation when the reference speed is reached.

22


ResultsFor better overview, the result section is divided in to two sub sections. The first sub section presents the performance requirement simulations for selected battery and fuel cell configurations. The second sub section presents the fuel consumption for the chosen fuel cell and battery configurations, control strategies and drive cycles.

PerformanceThe cruising ability requirement of 100 km/h at level ground is satisfied by the fuel cell of 200 kW maximum power. The speed and SOC profile for this fuel cell and a 4.5 kWh battery is presented in Figure 16, showing that the battery can be charged during the constant speed driving. Utilising a 150 kW fuel cell and 4.5 kWh battery configuration result in a discharge of the battery as shown in Figure 17.

Figure 16: Speed and soc profile during the constant speed simulation at zero incline utilising the 200 kW fuel cell and 4.5 kWh battery configuration.

23


Figure 17: Speed and soc profile during the constant speed simulation at zero incline utilising the 150 kW fuel cell and 4.5 kWh battery configuration.

24


The grade ability requirement of 40 km/h at the incline of 5 degree is not sustained by the 350 kW fuel. The speed and SOC profile for this fuel cell and a 15.8 kWh battery is presented in Figure 18, showing a discharge of the battery. The corresponding speed and SOC profiles for the 300 kW fuel cells and 4.5 kWh battery configuration, at the incline of 6 % (3.44o), is presented in Figure 19 showing that the battery can be charged during the constant speed driving. The corresponding speed and SOC profiles for the 250 kW fuel cells and 4.5 kWh battery configuration, at the incline of 5.5 % (3.15o), is presented in Figure 20 showing that the battery can be charged during the constant speed driving.

Figure 18: Speed and SOC profile during the constant speed simulation at 8.7 % incline utilising the 350 kW fuel cell and 15.8 kWh battery configuration.

.

25


Figure 19: Speed and SOC profile during the constant speed simulation at 6 % incline utilising the 300 kW fuel cell and 4.5 kWh battery configuration.

26


Figure 20: Speed and SOC profile during the constant speed simulation at 5.5 % incline utilising the 250 kW fuel cell and 4.5 kWh battery configuration.

27


The acceleration from stand still to 100 km/h at zero incline, utilising the 250 kW fuel cell and 6800 Wh battery configuration, is presented in Figure 21. Implementing a smaller battery cause the current drawn from the battery to exceed allowed values and an automatic ending of the simulation. The corresponding acceleration utilising the 250 fuel cell and 13.6 kWh battery configuration is presented in Figure 22. All configurations simulated in this report show a discharge of the battery.

Figure 21: Vehicle acceleration from stand still to 100 km/h at zero incline utilising the 250 kW fuel cell and 6.8 kWh battery configuration.

28


Figure 22: Vehicle acceleration from stand still to 100 km/h at zero incline utilising the 250 kW fuel cell and 13.6 kWh battery configuration.

29


The acceleration from stand still to 50 km/h at 8.7 % incline, utilising the 250 kW fuel cell and 6.8 kWh battery configuration, is presented in Figure 23. Implementing a smaller battery cause the current drawn from the battery to exceed allowed values and an automatic ending of the simulation. The corresponding acceleration utilising the 250 fuel cell and 13.6 kWh battery configuration is presented in Figure 24. All configurations simulated in this report show a discharge of the battery.

Figure 23: Vehicle acceleration from stand still to 50 km/h at 8.7 % incline utilising the 250 kW fuel cell and 6.8 kWh battery configuration.

30


Figure 24: Vehicle acceleration from stand still to 50 km/h at 8.7 % incline utilising the 250 kW fuel cell and 13.6 kWh battery configuration

31


Fuel consumptionThe fuel consumption for control strategy a, b and c, during the sort3 driving cycle is presented in table 13, 14 and 15 respectively. The battery and fuel cell configurations resulting in the lowest fuel consumption are marked whit green colour. The fuel consumption improvement is presented in percent of the fuel consumption of the reference truck. Figure 25-27 present the diesel equivalent consumption graphically and figure 28-30 present the fuel consumption improvement graphically.

Table 13: The resulting fuel consumption and the improvement in percent, for the sort3 drive cycle and control strategy a.Fuel cell Strings 2 3 4 5 6 7 8 9 10150 [kW] diesel [l/10km] 5,15 4,28 3,73 3,38 3,15 3,04 2,98 2,96 2,95 hydrogen [g/10km] 1539,54 1279,37 1116,12 1011,58 944,06 908,19 892,01 886,02 883,93 improvement [%] 9,42 24,73 34,33 40,48 44,46 46,57 47,52 47,87 47,99 200 [kW] diesel [l/10km] 5,17 3,90 3,45 3,17 3,00 2,91 2,87 2,86 2,86 hydrogen [g/10km] 1547,64 1168,22 1032,20 949,86 898,21 871,70 860,17 856,71 855,94 improvement [%] 8,94 31,27 39,27 44,11 47,15 48,71 49,39 49,59 49,64 250 [kW] diesel [l/10km] 4,98 3,80 3,43 3,19 3,03 2,96 2,92 2,91 2,91 hydrogen [g/10km] 1490,96 1136,43 1025,39 953,78 908,12 884,40 874,13 871,25 870,63 improvement [%] 12,28 33,14 39,67 43,88 46,57 47,96 48,57 48,74 48,78 300 [kW] diesel [l/10km] 4,91 3,83 3,48 3,26 3,12 3,04 3,01 3,00 3,00 hydrogen [g/10km] 1470,27 1146,38 1042,72 975,62 932,60 910,72 901,32 898,99 898,59 improvement [%] 13,49 32,55 38,65 42,60 45,13 46,42 46,97 47,11 47,13 350 [kW] diesel [l/10km] 4,93 3,91 3,57 3,36 3,22 3,16 3,13 3,12 3,12 hydrogen [g/10km] 1475,31 1168,74 1069,25 1004,51 964,10 944,23 935,63 933,68 933,46 improvement [%] 13,20 31,24 37,09 40,90 43,28 44,44 44,95 45,07 45,08

32


Table 14: The resulting fuel consumption and the improvement in percent, for the sort 3 drive cycle and control strategy b.Fuel cell Strings 2 3 4 5 6 7 8 9 10150 [kW] diesel [l/10km] 5,14 4,24 3,74 3,32 3,06 2,92 2,86 2,83 2,83 hydrogen [g/10km] 1538,39 1267,74 1118,99 993,44 915,88 874,10 855,22 848,07 845,78 improvement [%] 9,49 25,41 34,16 41,55 46,11 48,57 49,68 50,10 50,24 200 [kW] diesel [l/10km] 5,13 3,88 3,35 3,02 2,82 2,72 2,67 2,66 2,66 hydrogen [g/10km] 1535,93 1160,11 1003,06 904,10 844,41 812,63 799,14 794,65 794,98 improvement [%] 9,63 31,74 40,98 46,81 50,32 52,19 52,98 53,25 53,23 250 [kW] diesel [l/10km] 4,99 3,71 3,30 2,98 2,79 2,70 2,65 2,64 2,65 hydrogen [g/10km] 1493,79 1109,62 986,38 890,78 835,79 806,73 794,37 791,07 791,97 improvement [%] 12,11 34,71 41,97 47,59 50,83 52,54 53,26 53,46 53,40 300 [kW] diesel [l/10km] 4,92 3,71 3,37 3,04 2,83 2,74 2,70 2,69 2,71 hydrogen [g/10km] 1470,76 1109,07 1007,46 908,65 847,64 818,68 807,25 805,19 809,89 improvement [%] 13,47 34,75 40,72 46,54 50,13 51,83 52,50 52,63 52,35 350 [kW] diesel [l/10km] 4,94 3,75 3,42 3,20 2,94 2,82 2,79 2,81 2,85 hydrogen [g/10km] 1477,15 1123,04 1024,37 956,46 879,34 844,61 834,56 839,58 851,49 improvement [%] 13,09 33,92 39,73 43,73 48,26 50,31 50,90 50,60 49,90

Table 15: The resulting fuel consumption and the improvement in percent, for the sort 3 drive cycle and control strategy c.Fuel cell Strings 2 3 4 5 6 7 8 9 10150 [kW] diesel [l/10km] 5,12 4,19 3,65 3,28 3,07 2,93 2,86 2,83 2,83 hydrogen [g/10km] 1532,70 1253,86 1091,04 981,15 918,65 877,84 855,72 847,49 846,04 improvement [%] 9,82 26,23 35,81 42,27 45,95 48,35 49,65 50,14 50,22 200 [kW] diesel [l/10km] 5,14 3,78 3,27 2,96 2,75 2,64 2,59 2,58 2,58 hydrogen [g/10km] 1538,33 1131,43 978,17 886,80 823,64 789,87 775,23 770,82 770,54 improvement [%] 9,49 33,43 42,45 47,82 51,54 53,53 54,39 54,65 54,66 250 [kW] diesel [l/10km] 5,00 3,58 3,15 2,88 2,67 2,57 2,52 2,51 2,51 hydrogen [g/10km] 1496,12 1071,47 943,94 861,00 799,38 767,69 754,14 750,11 750,20 improvement [%] 11,97 36,96 44,46 49,34 52,97 54,83 55,63 55,87 55,86 300 [kW] diesel [l/10km] 4,89 3,55 3,14 2,87 2,66 2,55 2,51 2,50 2,50 hydrogen [g/10km] 1464,13 1062,70 939,11 859,50 795,46 763,65 750,43 746,74 747,24 improvement [%] 13,86 37,47 44,75 49,43 53,20 55,07 55,85 56,06 56,04 350 [kW] diesel [l/10km] 4,88 3,57 3,15 2,89 2,67 2,56 2,52 2,51 2,51 hydrogen [g/10km] 1461,01 1067,62 943,71 866,03 799,70 767,02 754,08 750,71 751,52 improvement [%] 14,04 37,19 44,48 49,05 52,95 54,87 55,63 55,83 55,78

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2 3 4 5 6 7 8 9 10150

250

3502,50

3,00

3,50

4,00

4,50

5,00

5,50

diesel equivalent [l/10 km]

battery stringsfuel cell [kW]

5,00-5,50

4,50-5,00

4,00-4,50

3,50-4,00

3,00-3,50

2,50-3,00

Figure 25: Fuel consumption for the sort3 drive cycle and control strategy a.

2 3 4 5 6 7 8 9 10150

250

3502,50

3,00

3,50

4,00

4,50

5,00

5,50



5,00-5,50

4,50-5,00

4,00-4,50

3,50-4,00

3,00-3,50

2,50-3,00

Figure 26: Fuel consumption for the sort3 drive cycle and control strategy b.

34


2 3 4 5 6 7 8 9 10150

250

3502,50

3,00

3,50

4,00

4,50

5,00

5,50



5,00-5,50

4,50-5,00

4,00-4,50

3,50-4,00

3,00-3,50

2,50-3,00

Figure 27: Fuel consumption for the sort3 drive cycle and control strategy c.

2 3 4 5 6 7 8 9 10150

250

3500,00

10,00

20,00

30,00

40,00

50,00

improvement[%]


40,00-50,00

30,00-40,00

20,00-30,00

10,00-20,00

0,00-10,00

Figure 28: Fuel consumption improvement for the sort3 drive cycle and control strategy a.

35


2 3 4 5 6 7 8 9 10150

250

3500,00

10,00

20,00

30,00

40,00

50,00

improvement[%]


40,00-50,00

30,00-40,00

20,00-30,0010,00-20,00

0,00-10,00

Figure 29: Fuel consumption improvement for the sort3 drive cycle and control strategy b.

2 3 4 5 6 7 8 9 10150

250

3500,00

10,00

20,00

30,00

40,00

50,00

improvement[%]


40,00-50,00

30,00-40,00

20,00-30,00

10,00-20,00

0,00-10,00

Figure 30: Fuel consumption improvement for the sort3 drive cycle and control strategy c.

36


The fuel consumption for control strategy a, b and c, during the sx365 driving cycle is presented in table 16, 17 and 18 respectively. The battery and fuel cell configurations not fulfilling the second criteria are marked whit red colour and the configurations resulting in the lowest fuel consumption are marked whit green colour. The fuel consumption improvement is presented in percent of the fuel consumption of the reference truck. Figure 31-33 present the diesel equivalent consumption graphically and figure 34-36 present the fuel consumption improvement graphically.

Table 16: The resulting fuel consumption and the improvement in percent, for the sx365 drive cycle and control strategy a.Fuel cell Strings 5 6 7 8 9 10

150 [kW] diesel [l/10km] 4,37 4,16 4,01 3,89 3,81 3,76 hydrogen [g/10km] 1306,32 1245,77 1198,49 1164,45 1141,10 1124,91 improvement [%] -1,76 2,95 6,64 9,29 11,11 12,37

200 [kW] diesel [l/10km] 4,12 3,94 3,82 3,73 3,67 3,62 hydrogen [g/10km] 1232,82 1179,31 1142,16 1115,46 1096,93 1083,50 improvement [%] 3,96 8,13 11,03 13,11 14,55 15,60




Table 17: The resulting fuel consumption and the improvement in percent, for the sx365 drive cycle and control strategy b.Fuel cell Strings 5 6 7 8 9 10






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Table 18: The resulting fuel consumption and the improvement in percent, for the sx365 drive cycle and control strategy c.Fuel cell Strings 5 6 7 8 9 10






56

78

910

150

250

350

3,00

3,20

3,40

3,60

3,80

4,00

4,20

4,40



4,20-4,40

4,00-4,20

3,80-4,00

3,60-3,80

3,40-3,60

3,20-3,40

3,00-3,20

Figure 31: Fuel consumption for the sx365 drive cycle and control strategy a.

38


56

78

9

10150

250

350

3,00

3,20

3,40

3,60

3,80

4,00

4,20

4,40



sx365 strategy b 4,20-4,40

4,00-4,20

3,80-4,00

3,60-3,80

3,40-3,60

3,20-3,40

3,00-3,20

Figure 32: Fuel consumption for the sx365 drive cycle and control strategy b.

56

78

910

150

250

350

3,00

3,20

3,40

3,60

3,80

4,00

4,20

4,40



4,20-4,40

4,00-4,20

3,80-4,00

3,60-3,80

3,40-3,60

3,20-3,40

3,00-3,20

Figure 33: Fuel consumption for the sx365 drive cycle and control strategy c.

39


5 6 7 8 9 10150

250

350

-5,00

0,00

5,00

10,00

15,00

20,00

25,00

30,00

improvement[%]


25,00-30,0020,00-25,0015,00-20,0010,00-15,005,00-10,000,00-5,00-5,00-0,00

Figure 34: Fuel consumption improvement for the sx365 drive cycle and control strategy a.

5 6 7 8 9 10150

250

350

-5,00

0,00

5,00

10,00

15,00

20,00

25,00

30,00

improvement [%]

battery strings

fuel cell [kW]

25,00-30,00

20,00-25,00

15,00-20,00

10,00-15,00

5,00-10,00

0,00-5,00

-5,00-0,00

Figure 35: Fuel consumption improvement for the sx365 drive cycle and control strategy b.

40


5 6 7 8 9 10150

250

350

-5,00

0,00

5,00

10,00

15,00

20,00

25,00

30,00

improvment [%]

battery strings

fuel cell [kW]

25,00-30,00

20,00-25,00

15,00-20,00

10,00-15,00

5,00-10,00

0,00-5,00

-5,00-0,00

Figure 36: Fuel consumption improvement for the sx365 drive cycle and control strategy c.

41


DiscussionPerformanceThe lowest fuel cell power needed to fulfil the constant speed requirement of 100 km/h at zero incline is 200 kW. Using a smaller fuel cell results in a discharge of the battery and imposes a duration limit of operation for the constant velocity requirement. The discharge is a result of the maximum fuel cell power being insufficient for the power demand of the electric propulsion motor.

The constant speed of 40 km/h at the incline of 8.7 % is not possible to sustain using the largest fuel cell proposed. The power required discharges the battery and limits the performance. This performance demand can be concluded to be a major issue for this application. Reducing the incline of this performance demand to 6 %, corresponding to the incline of Hallandsåsen, the constant speed (40 km/h) can be sustained utilising a fuel cell of 300 kW. For the fuel cell of 250 kW to be sufficient, the incline must be reduced to 5.5 %. It should be kept in mind that in a real application, the duration limit imposed by the 8.7 % incline can be sufficient if the summit is reached before the SOC drops to values below 20-30 %. For the configuration shown in figure 18, this corresponds to approximately eight minutes of climbing. Since, as discussed below, the vehicle equipped whit at least a 6.8 kWh battery is capable of accelerating from stand still at this incline, the driver can in a worst case stop to recharge the battery using fuel cell power.

The acceleration from standstill to 100 km/h on level ground can be obtained utilising the fuel cell with the maximum power of 250 kW and a 6.8 kWh battery. However the battery is discharged to values bellow 20 %. With the battery health in mined, this discharge is not to be recommended. By increasing the battery capacity to 13.6 kWh, the SOC can be kept above the acceptable 30%.

The acceleration from standstill to 50 km/h at the incline on 8.7 % can be obtained utilising the fuel cell with the maximal power of 250 kW and a 6.8 kWh battery. However, as for the previously discussed requirement, the battery is discharged to values bellow 20 %. Again, keeping the battery health in mined this discharge is not to be recommended. By increasing the battery capacity to 13.6 kWh, the SOC can be kept above the acceptable 30 %.

It is interesting to notice that the acceleration requirement at incline results in similar battery discharge as the acceleration requirement at zero incline. A reason for this can be that the drag force contribution during the higher speed requirement is replaced whit the gravitational force contribution during the incline requirement.

Fuel consumptionAn increase of the battery size reduces the fuel consumption for the sort3 drive cycle. The improvement is however less significant as the battery size becomes larger. Increasing the maximum fuel cell power does not necessarily improve the fuel consumption for this drive cycle. Among the simulated battery and fuel cell configurations, the best performing combination varies depending on the control strategy. The lowest fuel consumption calculated for the sort3 drive cycle, is obtained when utilising the fuel cell of 300 kW maximum power, a 20.4 kWh battery and control strategy c specified in table 9.

42


Keeping in mind that the cost, weight and volume of the system increase with lager battery capacities, while the fuel consumption benefit becomes less significant, it can be argued that implantation of more then 6 battery strings (13.6 kWh) is no longer complimentary. From an economical point of view, it might be difficult to motivate the fuel consumption benefit. The lowest fuel consumption for the sort3 drive cycle when utilizing the 13.6 kWh battery pack, is obtained with control strategy c and the fuel cell of 300 kW maximum power. As mentioned earlier this configuration is capable of cruising up an incline of 6 %, corresponding to Hallandsåsen, at a speed of 40 km/h. The fuel consumption is however insignificantly higher when implementing the fuel cell of 250 kW maximum power instead. Using a similar argumentation as for the battery size, it can be stated that the fuel cell of 250 kW is more suitable if the reduced performance capacity can be accepted.

To obtain the operating rang of the reference vehicle, (1383 km using an 810 l tank) calculated based on fuel consumptions of the sort3 drive cycle, a fuel cell vehicle powered by a 250 kW fuel cell and a 13.6 kWh battery requires 110 kg hydrogen stored on board. Storing the hydrogen at 70 MPa this corresponds to 16 assumed storage tubes. If the hydrogen is stored at 35 MPa, 26 tubes are required. The diesel fuel tank assumed for the reference vehicle is however the largest available and the more common solution for distribution application has approximately half of the assumed storage volume. Reducing the diesel storage by half, reduces the operation range of the reference vehicle by the same amount. Consequently, the amount of hydrogen storage tubes required to mach the operation range is also reduced by half.

For the sx365 drive cycle, increasing as well the battery size as the maximum fuel cell power both reduces the fuel consumption. The lowest fuel consumption calculated, is obtained when utilising the fuel cell of 350 kW maximum power, a 22.6 kWh battery and control strategy c. As for the previous drive cycle discussed, the fuel consumption improvement is less significant when the battery size increase. Consequently, using the same argumentation as above, it can be argued that implantation of more than 7 battery strings (15.8 kWh) is no longer complimentary. When looking at the fuel cells investigated in this study, the improvement of fuel consumption is not significantly reduced when the maximum fuel cell power increase. The implementation of a 350 kW fuel cell can therefore be motivated.

To obtain the operation rang of the reference vehicle, (1832 km using an 810 l tank) calculated based on fuel consumptions of the sx365 drive cycle, a fuel cell vehicle powered by a 350 kW fuel cell and a 15.8 kWh battery requires 175.26 kg hydrogen stored on board. Storing the hydrogen at MPa this corresponds to 25 assumed storage tubes. If the hydrogen is stored at 35 MPa, 41 tubes are required. As discussed above the more likely operation range for the reference vehicle is half of the assumed, reducing the amount of required hydrogen storage tubes by half.

It is interesting to observe that the fuel consumption of the diesel truck is lower on the sx365 drive cycle than it is on the sort3 drive cycle, while the opposite relation holds for the fuel cell application. This can be explained by the sx365 drive cycle being more demanding and hence more suitable for the diesel engine, which has high efficiency point at high load. The fuel cell system on the other hand has the highest efficiency at moderate loads, se figure 11. Based on this observation, the sort 3 drive cycle and the less hilly driving conditions this drive cycle represents can be stated more suitable for the fuel cell truck concept. The higher power demand of the sx365 drive cycle also explains the steady improvement of the fuel

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consumption when the maximum fuel cell power is increased for the sx365 drive cycle, while a local extreme value is reached for the sort3 drive cycle.

GeneralBeside the factors already mentioned motivating the choice of concept vehicle, yet another fact can be considered. This fact is the potential of using the selected vehicle in cooler vehicle application. The large energy demand of the refrigerating unit is usually matched by additional diesel engine operation. In the fuel cell application the power can be supplied by the fuel cell making it possible to farther increase the fuel and pollutant reduction factor. Due to lack of reference data, this is however not investigated in this report, even if the possibility is implemented in the model.

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ConclusionsThe fuel consumption can be reduced by up to 56 % by implementing a fuel cell drive line solution instead of the conventional diesel engine. The sort3 drive cycle is more suitable for the fuel cell truck application than the sx365 drive cycle.

For the sort3 drive cycle, the preferable fuel cell and battery configuration among the simulated ones is the fuel cell of 250 kW maximum power and the battery of 13.6 Wh. Utilizing a control strategy that shuts down the fuel cell when the fuel cell system efficiency drops to 20 % under the condition that the SOC is at least 50 %, this configuration reduces the fuel consumption by 53% compared to the reference vehicle. This configuration satisfies all performance requirements except the grade ability requirement of 40 km/h constant speed at the incline of 8.7 %. The grade ability requirement is thus too demanding. If the incline of the grade ability requirement is reduced to 5.5 %, this configuration satisfies the requirement.

For the sx365 drive cycle the preferable fuel cell and battery configuration among the simulated ones is the fuel cell of 350 kW and the battery of 15.8 kWh. The reduction of fuel consumption is 25.5 % when utilizing the same control strategy as the one stated for the previous drive cycle. This configuration satisfies all performance demands except the grade ability requirement. If the incline of the grade ability requirement is reduced to the incline of 6 %, this configuration satisfies the requirement.

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Future workDuring this study a constant factor of 1000000 has been used for the computation of the fuel cell power demand corresponding to the SOC deviation. This is a simplified power regulation that can be made more sophisticated e.g. by the use of a tan-1 function. A more sophisticated control strategy might allow for smaller batteries to be implemented, reducing the cost and weight of the system. It would be interesting to see to what extent this is true and how this might influence the fuel consumption. During the timeframe of this study the fuel consumption investigation has been prioritised and the economical aspect of the fuel cell concept has been included only on an intuitive basis in the discussion. The study and the conclusions drown would benefit greatly from a deeper economical investigation. A cost function including the long term economical aspect, the short term economical aspect, as well as the environmental benefit would complement the basis of the conclusion regarding the preferable concept.

A packing study investigating how the fuel cell system can be implemented on board the vehicle would also benefit this study. There are several conventional components that can be replaced and some new solutions might be needed. It would be of interest to investigate how the implementation can be accomplished and how it affect the cost, weight and load capacity of the vehicle.

The deep cycling of the battery of some configurations during the acceleration requirement, suggests that this will affect the way the vehicle can be used. The impact this cycling has on the battery health and lifetime is an interesting topic and so is the question of the actual needs of a suitable vehicle application.

The model used in this investigation, has in several of its parts been used in other related projects whit in Volvo Technology. No validations have however been found and none have been performed during this investigation. It is therefore strongly recommended for future study to look into such a validation. This applies equally to the new, as well as the adopted parts of the model and also to the related matlab files. Defining and constructing the validation process, might be a future topic in itself.

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References

[1] Antonio Sciarretta and Lino Guzzella, “Control of Hybrid Electric Vehicles”, IEEE Control System Magazine 27 issue 2 April (2007) 60-70

[2] Eva Håkansson, Hybridbilen – Framtiden är redan här, Ljungbergs Tryckeri: Klippan (2008)

[3] Volvo Press release, Future: The hybrid future is here, http://www.volvo.com/trucks/NewZealand-market/en-nz/newsmedia/pressreleases/press_article.htm?pubid=7872, 2009-11-02 (2009-12-14)

[4] Lisa Ehrlich, “I-SAM truck simulation report”, ER-530277, Volvo Technology Corporation, 2007

[5] Erik Nordin and Lars Carlhammar, “Design and performance of a fuel cell city distribution truck – a simulation study”, ER-58871, Volvo Technology Corporation, 2007

[6] On line gallery, http://www.volvo.com/trucks/sweden-market/sv-se/trucks/gallery/volvo_FM/volvo_FM_gallery.htm (2009-12-14)

[7] Iqbal Husain, ELECTRIC and HYBRID VEHICLES Design Fundamentals, CRC Press LLC: Florida (2003)

[8] Joachim Lindström, personal consultation, [email protected] [9] Pontus Enhager, “A preliminary study on a fuel cell buss”, 061020-01-2894-1, Volvo Teknisk Utveckling AB, 2001

[10] Jayanti et al., Cost Analyses of Fuel Cell Stack/System, DOE Hydrogen Program Annual Progress Report, (2008) 803-810

[11] Yunus A. Cengel and Michael A. Boles, THERMODYNAMICS An Engineering Approach, McGraw-Hill: Singapore (2006)

[12] Paul Adams, personal consultation, [email protected]

[13] L’Air liquide Division scientifique, Encyclopedie des gaz, Elsevier: New York (1976)

[14] James Larminie and Andrew Dicks, Fuel Cell Systems Explained Second Edition, John Wiles & Sins Ltd: England (2003)

[15] Jens Groot, “Generic Battery Model v.3.0”, 06120-06-11315-01, Volvo Technology Corporation 2006

[16] Green Car Congress, “Forecast: Lithium Ion Batteries for Electric Vehicles to Approach $8 Billion in Sales by 2015”, 3 December 2009, http://www.greencarcongress.com (19 January 2010)

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mailto:[email protected]

http://www.volvo.com/trucks/sweden-market/sv-se/trucks/gallery/volvo_FM/volvo_FM_gallery.htm

http://www.volvo.com/trucks/sweden-market/sv-se/trucks/gallery/volvo_FM/volvo_FM_gallery.htm

http://www.volvo.com/trucks/NewZealand-market/en-nz/newsmedia/pressreleases/press_article.htm?pubid=7872

http://www.volvo.com/trucks/NewZealand-market/en-nz/newsmedia/pressreleases/press_article.htm?pubid=7872


[17] Johan Johansson, “Modelling and Simulation of a Series Hybrid Electrical Vehicle in a City Bus Application”, Master Thesis, Chalmers University of Technology (2001)

[18] Jens Groot, personal consultation, [email protected]

[19] Richard T.M. Smokers, “Solving measurement and evaluation problems in development of test procedures for vehicles whit electric, hybrid and fuel cell power trains”, JOULE IV Program, paper nr. E10

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