rcube2: rapid prototyping ecu selected case studies … · rcube2: rapid prototyping ecu selected...

© Ricardo plc 2016

[email protected]

www.ricardo.com/rCube2

RD.16/191901.3

19 February 2019

rCube2: Rapid prototyping ECUSelected case studies

8© Ricardo plc 201619 February [email protected]/191901.3

Selected case studies (1)

Index Status Description

MC

M

PIO

M

SIO

M

TIO

M

HP

CM

E1 Pre-production Turbocharged CNG engine (6 cyl. / 10.5 litre) � �

E2 Testbed Turbocharged DI diesel engine (6 cyl. / 5.9 litre) � �

E3 Testbed Turbocharged DI gasoline engine (4 cyl. / 1.4 litre) � � �

E4 Testbed Turbocharged DI gasoline engine (4 cyl. / 2.0 litre) � �

E5 Testbed Turbocharged DI CNG engine (6 cyl. / 13 litre) � � �

E6 Testbed Turbocharged DI gasoline engine (4 cyl. / 2.0 litre) - lean aftertreatment � �

E7 Testbed Turbocharged DI diesel engine (4 cyl. / 3.0 litre) � � �

T1Vehicle

demonstration7-speed dual clutch transmission control � �

T2Vehicle

demonstration6-speed planetary automatic transmission control � �

H1Vehicle

demonstrationHybrid vehicle controller � �

H2Benchtest of

productionPlug-in hybrid electric vehicle control unit �

H3Benchtop

demonstrationBenchtest of 48 V / 25 kW mild hybrid inverter for a hybrid eDTC �

S1Vehicle

demonstrationSystem for novel autonomous vehicle system �

O1Benchtop

demonstration

Transmission control system running on rCube2 and its validation: rCube2 as a micro-

HiL��


Selected case studies (2)

Index Status Description

MC

M

PIO

M

SIO

M

TIO

M

HP

CM

A1 Proof of concept

Control system integrating engine control strategy, WAVE-RT and a physics-based

system simulation package focused on complete vehicle system modeling/simulation

(IGNITE) into rCube2

� � �

A2 Testbed Control system for single cylinder research CNG/diesel engine (1 cyl. / 0.5 litre) � �

A3 Testbed Control system for single cylinder research gasoline engine (1 cyl. / 0.45 litre) - Case 1 � �


A6 TestbedControl system with integrated real-time 1-D gas dynamics model (WAVE-RT) into

engine control strategy – Turbocharged DI gasoline engine (4 cyl. / 1.4 litre)��

A7 TestbedControl system with integrated real-time 1-D gas dynamics model (WAVE-RT) into

engine control strategy – Turbocharged DI diesel engine (6 cyl. / 5.9 litre)� � �



• Goal

– Create model-based control algorithm SW for turbocharged lean-burn CNG engine

• System description

– CNG engine, inline, 6 cyl./10.5 litre, turbocharged with intercooler

and mechanical WG, spark ignited lean-burn, single point injection

• rCube2 configuration

– MCM + SIOM

• Highlights

– EMS is developed in MATLAB/Simulink

– Control strategy manages all aspects of running CNG

engine primarily the fuelling, air and ignition demands

– Control system uses a model-based control approach

with a non-linear MVEM, Kalman filter observer and

full state feedback control to control in-cylinder lambda

– WAVE model based on measured data is used for MVEM calibration

– Control system tested on HiL and testbed in transient drive cycles

– Client pursued further development considering production

with client in-house control HW

• Sensors & Actuators

– CAM and CRANK positions, int. manifold P/T, pressures, temperatures, lambda/NOx, etc.

– Electric throttle valve, WG valve, injectors, ignition coils

Pre-production control system for turbocharged CNG engine

HiL system overview

E1: Engine control applications


Testbed control system for turbocharged DI diesel engine

• Goal

– Create model-based control algorithm SW for turbocharged DI diesel engine


– IVECO – F4AE0682C engine, diesel, inline, 6 cyl./5.9 litre, turbocharged with intercooler

– HPCR electronic fuel injection system

– Original WG is replaced by VGT


– MCM + SIOM

• Highlights


– WAVE / WAVE-RT models based on measured data are used in MiL for testing

– MiL: Co-simulation of WAVE/WAVE-RT, MATLAB/Simulink and IGNITE

– Tested in ETC and WHTC on testbed


– CAM and CRANK positions, fuel P in CR

– Int. manifold P/T, oil P/T

– Accelerator pedal, coolant T

– Fuel T and heating, VGT position

– Solenoid injectors, VGT, HPP valve

500 1000 1500 2000 2500 30000

200

400

600

800

1000

Engine speed [rpm]

En

gin

e torq

ue [N

m]

500 1000 1500 2000 2500 30000

40

80

120

160

200

Eng

ine

pow

er

[kW

]

Engine torque [Nm]

Engine power [kW]

WAVE-RT model



Testbed control system for turbocharged DI gasoline engine

• Goal

– Create model-based control algorithm SW for turbocharged DI gasoline engine


– VW – EA211 engine, gasoline, inline, 4 cyl./1.4 litre, turbocharged with intercooler

– HPCR electronic fuel inj. system


– MCM + PIOM + SIOM

• Highlights


– WAVE / WAVE-RT models based on measured data were used in MiL for testing

– MiL: Co-simulation of WAVE/WAVE-RT, MATLAB/Simulink and IGNITE

– Tested in WLTC and NEDC on testbed


– Int. and exh. CAM and CRANK positions

– Throttle position, WG position

– Fuel P in CR, int. manifold P/T, oil P/T

– Knock, lambda, coolant T, charge P/T

– Throttle valve, injectors, ignition coils

– Variable int. and exh. camshaft timing

– WG valve, HPP valve

WAVE-RT model




• Goal



– Mercedes Benz – M274 engine, gasoline, inline, 4 cyl./2.0 litre, turbocharged with intercooler

– HPCR electronic fuel inj. system; Max. torque.: 350 Nm at 1200 – 4000 rpm; Max. power: 155 kW at 5200 rpm


– MCM + PIOM

• Highlights


– Running at three combustion modes on testbed:

Stratified, Homogenous stratified and Homogenous (up to lambda = 3)

– Slave ECU concept: Crank-synchronous CAN communication

– rCube2 and developed EMS is used by a client on rapid prototyping projects


– Int. and exh. CAM and CRANK positions, int. manifold P/T

– HFM, EGR P/T, throttle position, WG position, knock, lambda

– Fuel P/T in CR, EGR position, coolant T, throttle in P/T

– Int. and exh. VVT, divert air switchover valve

– Throttle valve, EGR valve, WG vacuum actuator

– Piezo-injectors and smart ignition coils, HPP valve

Slave ECU concept

rCube2



• Goal

– Create model-based control algorithm SW for turbocharged DI CNG engine, Euro VI emissions legislation


– CNG engine, inline, 6 cyl./13 litre, peak torque: 2200 Nm

– Turbocharged with intercooler, rated power: 370 kW



• Highlights


– Supports stoichiometric and lean burn technologies

– Corona igniters, CNG injectors - SOGAV valves

– Fuelling control based on estimated cylinder air mass

– Charged air observer used for in-cylinder condition

monitoring and state estimation

– Max. lambda settings of 1.6 measured under part load operation

– Tested under steady-state and transient engine operating conditions on testbed



– Exh. manifold P/T, boost P/T, ambient P/T

– EGR P/T, oil P/T, fuel P/T, catalyst T, coolant T, lambda

– Solenoid injectors, corona ignition

– More than 9 valves including: Throttle, EGR, WGT, intake and exhaust VVT

Testbed control system for turbocharged DI CNG engine




• Goal



– Mercedes Benz – M274 engine, gasoline, inline, 4 cyl./2.0 litre, turbocharged with intercooler

– HPCR electronic fuel inj. system; Max. torque.: 350 Nm at 1200 – 4000 rpm; Max. power: 155 kW at 5200 rpm

– Lean gasoline aftertreatment


– MCM + PIOM

• Highlights


– Running at three combustion modes on testbed:

Stratified, Homogenous stratified and Homogenous (up to lambda = 3)

– Slave ECU concept: Crank-synchronous CAN communication

– Exhaust gas heat exchanger




– EGR P/T, throttle position, WG position, knock, lambda

– Fuel P/T in CR, EGR position, coolant T, throttle in P/T

– Int. and exh. VVT, divert air switchover valve

– Throttle valve, EGR valve, WG vacuum actuator

– Piezo-injectors and smart ignition coils, HPP valve, AdBlue injector

– NH3 sensor, NOx sensor, 2x SCR temperature sensor


Slave ECU concept


Testbed control system for turbocharged DI diesel engine

• Goal

– Create model-based control algorithm SW for turbocharged DI diesel engine


– Diesel, inline, 4 cyl./3.0 litre, turbocharged with intercooler and EGR




• Highlights


– Tested in steady states on testbed



– CAM and CRANK positions, fuel P in CR

– Int. manifold T, engine starter

– EGR in T, EGR in/out absolute pressures

– Throttle position, coolant T, fuel T

– Throttle valve, EGR valve

– Solenoid injectors, HPP valve



7-speed dual clutch transmission demonstrator vehicle

• Goal

– Create control algorithm SW for a prototype DCT


– Ricardo-designed demonstrator: 7-speed DCT is fitted to an existing vehicle provided by the customer

– Ricardo’s FAST-R transmission control SW developed in Simulink integrated into rCube2


– MCM + TIOM

• Highlights

– ‘Production intent’ DCT demonstrator vehicle with high level

of functionality

– CAN communication with gear shift lever and rest of vehicle

– Production-level sensing requirements for transmission

– Full range of transmission control functions provided

– Creep, pullaway, powershift, etc.


– 4 linear position (PWM), 4 rotational speed (frequency)

– 2 thermistors, 3 thermocouples

– 4 pressure sensors, one 3 axis accelerometer

– 2 CAN interfaces to rest of vehicle

– 11 current-controlled solenoid drives

T1: Transmission applications

Transmission with rCube2 in a vehicle


6-speed planetary automatic transmission demonstrator vehicle

• Goal

– Create control algorithm SW for a planetary automatic transmission


– 6-speed planetary automatic transmission to be initially used in an SUV application

– Ricardo’s FAST-R transmission control SW developed in Simulink integrated into rCube2


– MCM + TIOM

• Highlights

– Closed-loop simulation on HiL

– Basic SW test on a durability rig

– Full functionality to be implemented in demo vehicle initially

– Intention to port to production TCU

– Full range of transmission control functions provided

– Production-level sensing requirements for transmission

– Adaption, diagnostic, functional safety, start/stop and auto neutral developed

on production oriented TCU

– Two rCube2 units needed - HiL and rig/demo vehicle


– Output shaft speed sensor (PWM), input shaft speed sensor (PWM), bulk oil temperature sensor, shift lever position sensor

– 6 analogue variable force solenoids (normally high at 600 Hz PWM and normally low at 300 Hz PWM)

– 4 Boolean/digital solenoids, 6 current feedback inputs (1 per solenoid)

– CAN interface to rest of vehicle

T2: Transmission applications

rCube2 in a vehicle


• Goal

– Create control algorithm SW to support a mule vehicle containing engine/electric drive management,

48 V distribution and system supervision


– Turbocharged GDI engine

– 4 cyl./1.5 litre

– 48 V BMS

– Electric supercharger


– MCM + PIOM

• Highlights

– Torque, energy and hybrid functions management

– Extensive communication with other control units

– Supercharger bypass valve control with H-bridge

– Data acquisition from own sensors, analogue and digital I/O

– Boost control with electric supercharger, turbocharger WG and supercharger bypass valve

– Ricardo supported a client with steps required to productionise prototype system using units from OEMs

– Tested in NEDC and real drive cycle in a vehicle (on chassis dyno and on the road)


– Int. manifold P/T, electric supercharger P/T, electric supercharger bypass valve, digital I/O, etc.

Hybrid vehicle controller demonstration

CANbus 1 – Powertrain CANCANbus 2 – Hybrid CANCANbus 3 – Bypass CANHardwired

rCube2

Antilock BrakingSystem

Electric Power-Assisted Steering

Belt Starter Generatorwith integrated

Motor Controller

P/T Boost

P/T Supercharger

Superchargerbypass valve

Digital inputsDigital / LowSide

Outputs

Body Control Module

etc.

Engine Management

System

Electric Superchargerwith integrated

Motor Controller

DC to DCconverter

Battery ManagementSystem

HCU

Simplified schematic of entire system

H1: Hybrid & EV applications


• Goal

– Create a fully automated HiL setup for functional verification of PHEV control strategy


– Bosch VCU with application SW developed by Ricardo

– Test harness written in MATLAB using Vehicle Network

Toolbox and Simulink Desktop Real-Time


– MCM

• Highlights

– Calibratable plant model developed in

MATLAB/Simulink and running in rCube2

– rCube2 capable to exercise all VCU HW I/O and

substitute all nodes of vehicle CAN network apart from VCU

– VCU application SW is using same development platform as rCube2 SW

– Automated and manual testing using developed MATLAB GUI interface

– Ricardo supporting client with steps required to productionise developed VCU control system

Benchtest of production plug-in hybrid electric vehicle control unit



• Goal

– Create a controller for novel 48 V / 25 kW MOSFET inverter, 25 kW motor and capacitor bank that is suitable for a hybrid powertrains (passenger cars and commercial) with emission levels below Euro VI


– Inverter for mild hybrid eDCT sharing the oil cooling

circuit and achieving high heat transfer

– ‘Safe’ low voltage used as a main power source


– MCM

• Highlights

– 3/6-phase frameless AC Interior Permanent Magnet machine; hairpin

windings; very compact end windings; 25 000 rpm; low manufacturing cost

– Up to 600 A RMS current per phase

– 24 kHz PWM control; compact power pack; specific power of 6.4 kW / litre

– Oil and water cooled variants

– Electronics open to sensor or sensor-less control

– BLDC and induction motors drive

– Advanced techniques of non-linear motor control

– Test results of the motor and power electronics validated that the resulting

mild hybrid vehicle would be capable of achieving a market leading efficiency

– an increase of 27 % compared to the base, non-hybrid vehicle


– Configurable resolver interface with advanced diagnostic; 6x analogue current sensor interface; 6x temperature sensor inputs

Benchtest of 48 V / 25 kW mild hybrid inverter for a hybrid eDCT



Gate driver board

DCLINK 48V supply

eMotor sensor connector

DCLINK capacitor bank

rCube2 connector

Mezzanine board

Phase cables attachments


rCube2

• Goal

– Vehicle position estimation and data logging for a novel non-automotive

autonomous vehicle system using automotive sensors


– System required to provide safety critical information on detected objects giving bearing, size, distance and

relative speed


– MCM

• Highlights

– Huge amount of data acquisition and real-time processing

– Sensor fusion algorithm implemented in MATLAB/Simulink

– Demanding Ethernet and TCP/IP communication requirements

– Laser sensor and combined short/long range radar used as sensors and combined with other system inputs

– Data output over Ethernet to ‘vehicle control system’ and ‘data logger’

– Ricardo supporting client with steps required to productionise developed prototype system

Vehicle demonstration of novel autonomous vehicle system

Simplified schematic of sensing system

S1: Telematics and multi-sensor data fusion applications


Benchtop demonstration of transmission control running on rCube2: micro-HiL

• Goal

– Run and validate Automatic Transmission control algorithms (developed in TargetLink) on rCube2

– TargetLink is used instead of common MATLAB/Simulink/Embedded Coder approach


– Vehicle plant model is developed in Ricardo simulation tool V-Sim based on MATLAB/Simulink

– Prototype transmission control algorithm is developed in TargetLink


– 2x MCM

– Two rCube2 units in network

• Highlights

– Integration into rCube2/AUTOSAR

– 1st rCube2 to run plant model

– 2nd rCube2 to run control functions

– Closed-loop simulation between

two rCube2 units

– Connection to all sensors and

actuators via CAN

– INCA and CANape calibration

tools were applied

1 2

34

67

8

9 1011 12

No Item

1 V-Sim as plant model

2 AT control function model

3 rCube2 to run plant model

4 rCube2 to run control model

5 Power supply

6 Breakout box for rCube2running plant model

7 Breakout box for rCube2running control model

8 CAN line

9 ES581 for INCA host PC(rCube2 running plant model)

10 ES581 for INCA host PC(rCube2 running control model)

11 INCA host PC (rCube2 running plant model)

12 INCA host PC (rCube2 running control model)


O1: Other applications


Proof of concept: Control system with integrated WAVE-RT and IGNITE

• Goal

– Create model-based control algorithm SW for gasoline engine running WAVE-RT engine model and IGNITE vehicle model real-time in the engine control strategy


– Bench simulation of VW Golf Mk6 vehicle



– MCM + PIOM + HPCM

• Highlights

– WAVE / WAVE-RT models are created and validated based on measured data

– EMS is developed in MATLAB/Simulink while WAVE-RT offers precise real-time engine modelling and IGNITE models the rest of vehicle functionality (e.g. driveline and cooling circuit models)

– Tested on HW demo in WLTC


– Int. and exh. CAM and CRANK positions

– Throttle position, WG position

– Fuel P in CR, int. manifold P/T, oil P/T

– Knock, lambda, coolant T, charge P/T

– Throttle valve, injectors, ignition coils

– Variable int. and exh. camshaft timing

– WG valve, HPP valve

Measured data vs. WAVE vs. WAVE-RT

IGNITE: Vehicle model - model of driveline

Tasks running real-time in rCube2

A1: Advanced control applications


• Goal

– Create model-based control algorithm SW for CNG/Diesel - dual fuel single cylinder research engine (cooperation with Czech Technical University in Prague)


– AVL single cylinder Common Rail DI research engine, 1 cyl./0.5 litre

– Independent boosting with back pressure control for emulation of realistic turbocharging


– MCM + SIOM

• Highlights


– Multiple injections per cycle

– Original ECU replaced by rCube2

– EMS manages all aspects of running the engine

– Dual fuel application: CNG PFI and diesel pilot injection control

– rCube2 and developed EMS used for the dual fuel combustion research


– CAM and CRANK positions, diesel fuel rail P, CNG rail P

– Int. manifold P/T, oil P/T, accelerator pedal, coolant T, lambda

– Fuel T and heating, exh. gas P/T

– Diesel and CNG injectors, metering unit valve, HPP valve, EGR valve

Testbed control system for single cyl. research CNG/diesel engine



Testbed control system for single cyl. research gasoline engineCase 1

• Goal

– Create model-based control algorithm SW for Ricardo single cylinder research gasoline engine


– Ricardo GDI engine (Hydra), 1 cyl./0.45 litre, homogeneous and stratified charge, boosted induction

– 4 valves/cyl.; Engine speed: 1000 - 6200 rpm; Fuel pressure: 40 - 200 bar; Multiple injections


– MCM + PIOM

• Highlights


– 5 injections per cycle, twin CAM phasers, hydraulic activation

– Solenoid and position sensor closed-loop VVT control

– 200 bar pressure fuel rail control

– Closed-loop fuelling using lambda sensor

– Tested on testbed

– rCube2 fuel injection solenoid driver triggers ‘NI Drivven’ module in direct mode to drive solenoid injectors

– Fuel pump is camshaft driven with crank synchronous solenoid spill valve control, dead ended fuel rail

– rCube2 together with developed control system is used by a client on its rapid prototyping projects


– Injectors, smart ignition coils, electronic throttle valve, EGR valve, HPP valve, camshaft timing, etc.




• Goal



– Ricardo GDI engine (Hydra), 1 cyl./0.5 litre, stoichiometric and lean-stratified charge, turbo-supercharging

– 4 valves/cyl.; Compression ratio: 13:1; Rated power 100 kW/litre; Tumble ratio Rt > 1; Multiple injections

– Central injector combustion system; Peak BMEP: 25 bar


– MCM + PIOM

• Highlights


– 5 injections per cycle, twin CAM phasers, hydraulic activation


– 200 bar pressure fuel rail control

– Closed-loop fuelling using lambda sensor

– Tested on testbed

– rCube2 fuel injection solenoid driver triggers ‘NI Drivven’ module in direct mode to drive solenoid injectors

– Fuel pump is camshaft driven with crank synchronous solenoid spill valve control, dead ended fuel rail


– Solenoid injectors, smart ignition coils, electronic throttle valve, EGR valve, HPP valve, camshaft timing, etc.



Testbed control system with integrated WAVE-RT – gasoline engine

• Goal

– Create model-based control algorithm SW for turbocharged DI gasoline engine running

WAVE-RT engine model real-time in the engine control strategy




• rCube2 configuration: Two rCube2 units


– MCM + HPCM

• Highlights


– WAVE / WAVE-RT models based on measured data were used in MiL for testing

– WAVE-RT integrated into EMS

– Multi-rCube2 system demonstration

– Tested in WLTC / NEDC / RDE vehicle driving cycles on testbed


– Int. and exh. CAM and CRANK positions, throttle position

– WG position, fuel P in CR, int. manifold P/T, oil P/T, knock

– Lambda, coolant T, charge P/T, throttle valve, injectors, HPP valve

– Ignition coils, variable int. and exh. camshaft timing, WG valve



Testbed control system with integrated WAVE-RT – diesel engine

• Goal

– Create model-based control algorithm SW for turbocharged DI diesel engine running

WAVE-RT engine model real-time in the engine control strategy


– IVECO – F4AE0682C engine, diesel, inline, 6 cyl./5.9 litre, turbocharged with intercooler

– HPCR electronic fuel injection system

– Original WG is replaced by VGT


– MCM + SIOM + HPCM

• Highlights


– WAVE / WAVE-RT models based on measured data are used in MiL for testing; WAVE-RT integrated to EMS

– Using in-cylinder air mass calculated in WAVE-RT instead of air mass estimation from intake pressure allowed up to 5.5% smoke improvement in WHTC drive cycle

– Standard intake boost pressure sensor replaced by virtual sensor from WAVE-RT achieving the similar engine

responses and engine exhaust emissions

– Tested in ETC and WHTC on testbed


– CAM and CRANK positions, fuel P in CR, VGT position

– Int. manifold P/T, oil P/T, accel. pedal, coolant T

– Fuel T and heating, solenoid injectors, VGT, HPP valve

500 1000 1500 2000 2500 30000

200

400

600

800

1000

Engine speed [rpm]

En

gin

e to

rque

[N

m]

500 1000 1500 2000 2500 30000

40

80

120

160

200

Eng

ine

pow

er

[kW

]

Engine torque [Nm]

Engine power [kW]

Simplified schematic of smoke limitationSimplified schematic of boost pressure

sensor replacement




• Goal



– Ricardo GDI engine (Hydra), 1 cyl./0.5 litre, homogeneous and stratified charge, boosted induction, 4 valves/cyl.; Compression ratio: 17:1

– Engine speed: 1000 - 4200 rpm; Fuel pressure: 40 - 200 bar; Multiple injections (3 split for gasoline, 1 injection for water - port or direct)

– Miller EIVC CAM timing; Advanced combustion system concept achieving 45 % brake thermal efficiency


– MCM + PIOM

• Highlights


– Strategy, harness preparation and HiL testing completed before engine install

– Trouble free engine start and control achieved with complex technology

– Flexible set-up enabled rapid build changes and ignition type switches

– DI gasoline, DI water and port water injection

– Three types of ignition: Standard ignition coil, Corona OEM#1 and OEM#2

– LP cooled EGR; Twin CAM phasers, hydraulic activation


– Throttle valve closed-loop position control, EGR valve closed-loop position control

– 200 bar pressure fuel rail control; Closed-loop fuelling using lambda sensor

– Fuel pump is camshaft driven with crank synchronous solenoid spill valve control

– rCube2 with developed EMS is used by a client on its rapid prototyping projects


– CAM and CRANK positions, lambda, DI water rail P, fuel and water P feedback, etc.

– Fuel and water injectors, spark plug coil/corona ignitors, electronic throttle valve, EGR valve, fuel and water HPP valve, camshaft timing, etc.



Acronyms and abbreviations

• AC = Alternating Current

• AUTOSAR = AUTomotive Open System Architecture

• BLDC = Brushless DC Electric Motor

• BMEP = Brake Mean Effective Pressure

• BMS = Battery Management System

• CAM = Camshaft

• CAN = Controller Area Network communication bus

• CANape = a measurement, calibration and diagnostic software from Vector Informatik

• CNG = Compressed Natural Gas

• CR = Common Rail

• CRANK = Crankshaft

• DC = Direct Current

• DI = Direct Injection

• DCT = Dual Clutch Transmission

• eDCT = electric Dual Clutch Transmission

• ECU = Electronic Control Unit

• EGR = Exhaust Gas Recirculation

• EIVC = Early Intake Valve Closing

• EMS = Engine Management System

• ETC = European Transient Cycle

• FAST-R = Flexible Advanced SW for Transmissions by Ricardo

• GDI = Gasoline Direct Injection

• GUI = Graphical User Interface

• HCU = Hybrid Control Unit

• HFM = Hot Film air Mass

• HiL = Hardware in the Loop

• HPCM = High Power Computing Module

• HPCR = High Pressure Common Rail

• HPP = High Pressure Pump

• HW = Hardware

• I/O = Input/Output

• IGNITE = a physics-based system simulation package

focused on complete vehicle system modeling and simulation from Ricardo

• INCA = a measurement, calibration and diagnostic software

from ETAS

• MCM = MicroController Module

• MiL = Model in the Loop

• MOSFET = Metal Oxide Semiconductor Field Effect Transistor

• MVEM = Mean Value Engine Model

• NEDC = New European Driving Cycle

• OEM = Original Equipment Manufacturer

• P = Pressure

• P/T = Pressure and Temperature

• PFI = Port Fuel Injection

• PHEV = Plug-in Hybrid Electric Vehicle

• PID = Proportional–Integral–Derivative

• PIOM = Powertrain I/O Module

• PWM = Pulse Width Modulation

• RMS = Root Mean Square

• SCR = Selective Catalytic Reduction

• SiL = Software in the Loop

• SIOM = Solenoid injectors I/O Module

• SOGAV = Solenoid Operated Gas Admission Valve

• SUV = Sport Utility Vehicle

• SW = Software

• T = Temperature

• TargetLink = a software for automatic code generation produced by dSPACE

• TCP/IP = Transmission Control Protocol/Internet

Protocol

• TCU = Transmission Control Unit

• VCU = Vehicle Control Unit

• VGT = Variable Geometry Turbocharger

• VVT = Variable Valve Timing

• WAVE = a crank-angle based, 1D engine & gas dynamics simulation software package from Ricardo

• WAVE-RT = a real-time, crank-angle based, 1D engine & gas dynamics simulation software package from Ricardo

• WG = WasteGate

• WHTC = Worldwide Harmonized Transient Cycle

• WLTC = Worldwide harmonized Light duty Test Cycle

• XCP = Extended Calibration Protocol

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