adaptive cruise controller module design for the electric vehicle oskar 1 project supervisors:...

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Adaptive Cruise Controller Module Design forthe Electric Vehicle OSKAR

Project Supervisors: Assoc. Prof. Dr. Rifat EDİZKAN Asst. Prof. Dr. Ahmet YAZICI

Project Assistant: İslam KILIÇ

Team Members: Mustafa ÖZÇELİKÖRS Atakan ONDOĞAN İbrahim YILDIRIM

Deniz Can DAYAN Metin KUNDAKÇIOĞLU

Material support by;

Eskisehir Osmangazi UniversityElectrical and Electronics Engineering

Engineering Design Senior Project

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Presentation Outline• Introduction and Motivation• System Overview• Detailed System Design

– Low-Level Infrastructure (RTOS, Sensors & Communication, Motor Drive)• Real Time Operating System• Sensors & Communication

– CAN-BUS Communication– Continental ARS308 Long Range RADAR Sensor Driver + Logging– TCP Communication for Low-Level– Hall-Effect Encoder System

• Motor Drive using DAC– Low-Level Design (Purpose, PID Controllers, PID Tuning, Cohen-coon)– Low-Level Implementation (Throttle-based Control + PID Algorithm)– Low-Level Tests– High-Level Infrastructure (Raspbian system, Rpi, Why Python?)– High-Level Design and Implementation (Purpose, PFM Algorithm, Proposed Radar

Perception Algorithm)– High-Level Display Unit– System Realization with PCB

• Conclusion

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Introduction & Motivation

What is ACC?

Adaptive Cruise Control (ACC) is an advanced velocity control system for vehicles that automatically adjust the vehicle’s speed in order to maintain a proper distance from vehicles and obstacles on the road.

A vehicle on ACC moves at a pre-adjusted velocity while there is no obstacle or vehicle ahead. If the sensor detects an obstacle or vehicle, the system controls the velocity of the ACC controlled vehicle in order to accelerate, decelerate or stop –according to the speed of the obstacles or cars.

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WHY ACC ?

Avoid Accidents,Safe DriveBetter driving

comfort (especially on long-distances)

All-domestic carTo gain know-how on the subject of

‘intelligent vehicles’

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How does ACC system work?

Adaptive Cruise Control (ACC) system uses various sensors (RADAR, LIDAR, GPS, Camera) to detect objects ahead. When an object is detected, sensor sends the information about the target (such as distance, velocity and acceleration) to the controllers.

Controllers take these information and by using the host car’s own velocity, calculate a safe distance and desired velocity values.Then, these values are processed and applied to the vehicle motor in order to track desired velocity and distance values successfully.

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ACC on Commercial Area:

• In the beginning of the 1990’s, even the CC was a luxury and having the CC feature caused a big price difference to a car.

• By the 2000’s CC has became more and more common and affordable. So does ACC.

• Nowadays, some car manifacturers use ACC system with their own commercial names and different features. These systems vary in:– Number and features of sensors used.– Specialized speed ranges for high performances.– Extra features (such as strip tracking)

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System Overview

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System OverviewWhat are needed?

A Cruise State Input:PushbuttonAn actuator: Motor&driverA reference input: Throttle/PedalA feedback sensor:Hall Effect Encoder SystemA vision sensor: ARS-308 Radar SensorAn Engine&Sensor Controller:STM32F4-DISCOVERY withSTM32F4DIS-BBA High-Level Decision Unit:Raspberry PiA visualization & input unit: 3.5” TFT Touchscreen

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System Overview - ComponentsSTM32F4-DISCOVERYProvides- STM32F407VGT6 168MHz32-bit ARM Cortex-M4F corew/ 1MB Flash 192KB RAM- ADC, DAC, DMA, ETH, USART, CAN, SPI, USB-OTG peripherals that are used in the system.- CMSIS Support: Code is compatible with all the other ARM devices.

STM32F4DIS-BBProvides- Expansion for STM32F4-DISCO- Ethernet, MicroSD that are used in the system.

Raspberry Pi Model B+Provides-700MHz ARM11 Processor- Open VG GPU- 512 MB SDRAM- 40 pin GPIO

4DPi-35 3.5” Touchscreen TFTProvides- 3.5” TFT Display with Touchscreen- Boot-ready kernel for easy interfacing

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System Overview – Block Diagram

Hig

h Le

vel Low Level

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Low Level Infrastructure

• Real Time Operating System• Sensors & Communication

– CAN-BUS Communication– Continental ARS308 Long Range

RADAR Sensor Driver + Logging– TCP Communication for Low-

Level– Hall-Effect Encoder System

• Motor Drive using DAC

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Real Time Operating System

• Real time in embedded systems means that the embedded system must respond to a certain event within a strictly defined time.

• In embedded systems, we often have real-time requirements.

• RTOS provides execution patterns and scheduling while executing real-time tasks.

• It resembles to an operating system.• RTOS has an advanced scheduler that

manages interruption.• FreeRTOS is a highly-known, easy-to-use,

migrateable library for real time operations in embedded systems.

• Configured Priorities, Stack Sizes, Heap Size, Task Creation

• Used Embedded Workbench for ARM

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Real Time Operating System

• Priorities in the program must be determined delicately to prevent the program from running in the idle task.

• Priorities of the system:PID Routine = Encoder Data Reception > TCP Comm. = ADC Conv. > LEDs&Switches• CAN-BUS is operated with an interrupt routine.• In our system, we defined the task periods with the following fashion,Tasks with Strict Periods > Tasks that require Pending > Other Tasks

Start

Set Priorities, Stack Sizes,Heap Size

Define RTOS Tick Period (1ms in our

system)

Define Task Routines

Start RTOS Scheduler

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CAN-BUS Communication

• Controller Area Network (CAN) (ISO-11898: 2003) is a 2-wire bus that is used in automotive industry to replace complex wiring harness.

• A transceiver should be used in each node.

• Advantages: High reliability, resistance against electromagnetic interference, real-time capability, multi-speed configurations, high-speed.

• 11-bit and 29-bit Identifier CAN-BUS frames are available. We use 11-bit Identifier.

• CAN Baudrate configuration is crucial. A design equation has been derived.

• CAN-BUS library for STM32 is used.

( 1 2)*Prescaler

ClockFrequencyCANBaudrate

SJW BS BS

ClockFrequency = 42MHz (in the CAN1 line)SJW=1 BS1=6 BS2=7Prescaler = 6CANBaudrate = 500KBps

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CAN-BUS Communication Implementation

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Continental ARS-308 Long Range RadarDriver Implementation

• The ARS 308 is a Radar Sensor System developed by Continental for the Automotive Industry to realize advanced driver assistance functions.

• Provides information on targets/objects once configured.

• Provides Motorola big-endian data through CAN-BUS.

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How to construct actual object data from raw data?

Bitwise OperationsObtained

bit information for each data

Multiply by Resolution

Add the Offset

Obtained actual information of type float/integer/double

#define res1 , res2, ... #define off1, off2, ... _MesajID409H.WarnMsgCounter = (uint8_t) (Data[0]&0x1F); _MesajID409H.RegionID = (uint8_t) ((Data[0]&0xE0)>>5); _MesajID409H.WarningLevel = (uint8_t) (Data[1]&0x03); _MesajID409H.ObjectID = (uint8_t) ((Data[1]&0xFC)>>2); _MesajID409H.ObjLatPos = (uint32_t) ((Data[2]<<2)|((Data[3]&0xC0)>>6)); _MesajID409H.ObjLongSpd = (uint32_t) (((Data[3]&0x3F)<<6)|((Data[4]&0xFC)>>2)); _MesajID409H.ObjLatSpd = (uint32_t) (((Data[4]&0x03)<<6)|((Data[5]&0xFC)>>2));

_ProcessedObject [_MesajID409H.ObjectID].ObjectID = _MesajID409H.ObjectID;_ ProcessedObject [_MesajID409H.ObjectID].ObjLatPos = (_MesajID409H.ObjLatPos)*res1 - off1;_ ProcessedObject [_MesajID409H.ObjectID].ObjLatSpd = (_MesajID409H.ObjLatSpd)*res2 - off2;_ ProcessedObject [_MesajID409H.ObjectID].ObjLongPos = (_MesajID409H.ObjLongPos)*res3;_ ProcessedObject [_MesajID409H.ObjectID].ObjLongSpd = (_MesajID409H.ObjLongSpd)*res4 - off4;_ ProcessedObject [_MesajID409H.ObjectID].ObjWidth = (_MesajID409H.ObjWidth)*res5;

Write data to object

array with index as

Object ID

Object Data (array)

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Implemented ARS-308 Driver,• Consists of CAN-BUS Transmit and Receive functions.• Consists of CAN-BUS Data Preparation and Clearance functions.• Consists of Raw to Actual Data Resolution functions. (for receiving messages)• Consists of Actual to Raw Data Preparation functions. (for config messages)• Can save all the data to predefined structs.• Has an Object array that is filled with all the information about all the object.• Uses the Object array to apply proposed filter and find the filtered object.

struct Object{ uint8_t ObjectID; uint32_t ObjLatPos; uint32_t ObjLongSpd; uint32_t ObjLatSpd; uint32_t ObjLongPos; uint8_t ObjWidth;};

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Continental ARS-308 Long Range RadarSensor Logging (Raw+Processed Data)

No Mode Mesaj ID(Hex)

RTR DLC D1 D2 D3 D4 D5 D6 D7 D8 Time stamp

1 0 00 00 00 00 00 00 00 00 00

//Determine Object IDiz = _MesajID60BH.Obj_ID;//Write ObjLongPosFloatToStr(_ProcessedObject[iz].ObjLongPos);f_write(&file, STRING_BUF, strlen(STRING_BUF), &bw);f_write(&file, "\t", strlen("\t"), &bw);

• Sensor logging is needed for further understanding of how Radar data works.• We use SD Card for Radar Sensor Logging. (STM32F4DIS-BB)• FatFs library is used for SDIO operations.• A piece of software that can log raw and processed data at the same time to different files has

been created.

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TCP (Ethernet) Communication• Between Low Level and High Level, TCP Communication is established.• As hardware, STM32F4-DISBB is used, equipped with LAN8720 chip.• Since it is easy to be interfaced in a computer (such as Raspberry Pi) and provides Server-Client

structure, it is selected for the project.• TCP Communication is established with static IP addresses on both server and client. Also, a MAC

address have to be provided.• Highly-known LwIP library (TCP/IP Lib for embedded systems) and Netconn API is used in the

implementation of the TCP Server software.• When sending and receving a data, a struct called pbuf is configured.• XML Design:

<data> <items> <item V_Host=""></item> <item V_CC_Setpoint=""></item> <item Cruise_Button_State=""></item> <item Vehicle_Accel=""></item> <item X=""></item> <item V_Relative=""></item></items></data>

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Motor Drive Using DAC• OSKAR has a Motor Driver Model D51448.01 of PG Drives Technology.• 2.24V ~ 5V -> Forward incremental• 2.24V ~ 0V -> Backward incremental• Motor Driver 0V~5V , STM32 VDD=3V• An Amplifier is Needed:

(hardware designs are the collective work of all the team members)

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Motor Drive Using DAC• Throttle Pedal works

within 0.8V~4.2V range. • STM32 has ADC with V_IN

= 3V• A voltage divider is

Needed: (0.57V~3V)

(hardware designs are the collective work of all the team members)

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Encoder Implementation

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Low-Level Design

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Low-Level Design

Two paths for low-level control algortihm design are defined.

Compensating the system with PID controller using both Root-Locus method and PID Tuner tool of MATLAB.

Modeling the system by using a common mathematical model for the motor (24V DC, Brushed).

This study is conducted to get the optimum PID controller parameters for first order process model.

Determining the proportional, integral, and differential parameters in the controller by Cohen-Coon open loop tuning method which is described the controller parameters in the form of formulas or algorithms.

First Path: Second Path:

27End

Modeling the System

Obtaining the Controller’s Gains

Outdoor Tests

Indoor Tests

Determining the Control Method

Start

Are the results

satisfying?

Are the results

satisfying?

No

Yes

Yes

No

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First Path for Low-Level Design

Model circuitry for a brushed DC motor:

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Block diagram of the motor’s mathematical model:

Transfer function of the system in Laplace domain:

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Designing the PID controller for the model with Root-Locus method:

Simulations in MATLAB:Acceptable settling time and percent overshoot values for the step response.

Indoor tests:• Desired performance specifications

could not be satisfied.• Oscillations occured.• Response did not settle.• Extreme percent overshoot value.

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Designing the PID controller for the model, using PID Tuner tool:

Simulations in MATLAB:Since the purpose of the tuner is to obtain the exact controller gains, simulation resulted in exact success.


are mostly satisfied.• Negligible oscillations in steady-

state.• Good performance in high velocity

setpoints.• Relatively high settling time and

percent overshoot for the smaller velocity setpoints

Cohen Coon Method

The Cohen-Coon method is classified as an offline method for tuning, meaning that a step change can be introduced to the input once it is at steady-state. Then by looking at the system’s response, once the values of process parameters are obtained, the PID parameters can be calculated based on Cohen-Coon Tuning Rules.

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Second Path for Low-Level Design

Cohen-Coon Representative System Output and Input

System Output for OSKAR when the step input was applied

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The step input is applied to the system until the process

reaches steady state

Obtaining the step graphic of the system

Start

5 parameters (t0, t2, t3, A and B) are

determined by the direct use of graph

Using the measurements of t0, t2, t3, A and B, the process parameters t1, τ, τdel, K and r are calculated by

using MATLAB

System reaches

steady state?

The controller parameters Kc, τ int and τder are obtained by

the implementation of specified formulas of Cohen-

Coon Tuning Rules

Getting the gain constants of PID controller (Kp, Ki

and Kd)

End

No

Yes

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Determining the PID controller parameters for the model with Cohen-Coon method:


could not be satisfied.• Oscillations occured.• Extreme percent overshoot and

settling time values

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Low-Level Implementation

Kp = 0.1 , Ki = 0.2 , Kd = 0.0047

Formula Discretized Formula

Proportional

Integral

Derivative

P )(teK p )(teK p

I t

i deK0

)(

t

isi ieTK

0

)(

D

dt

tdeKd

)(

sd T

teteK

)1()(

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Pseudo code of the PID controller:

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Outdoor Tests

Velocity setpoint is 5 km/h

• Percent overshoot about 40%

• Negligible steady-state error

• Successful settling time• Good performance for

uphill/downhill cases

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Outdoor Tests

Velocity setpoint is 10 km/h

• Zero overshoot• Steady-state error about

%3• Successful settling time• Best performance for

uphill/downhill cases

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Outdoor Tests

Comments:• OSKAR’s maximum speed with load

on a plane road is about 15 km/h.• Performance of the control system

works is best at the velocity values around 10 km/h.

• Vehicle’s mechanical limitations affects the system performance.

• Weight of the load is inversely correlated with the performance of the low-level control system.

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High Level Design

Control Methods • Time Delay Control (TDC) • Fuzzy Logic Control• Sliding Mode Control (SMC)• Constant Time Gap Control (CTG)• Proportional Integral (PI) Control • Proportional Derivative (PD) Control• Proportional Integral Derivative (PID) Control• Model Predictive Control (MPC)

ACC can be implemented with various control methods

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• Conventional Cruise ControlMaintaining a steady speed set by driver

High Level DesignPurpose High Level Unit has two main tasks:

• Adaptive Cruise ControlTwo modes of control: Velocity and DistanceAdjusting velocity in order to maintain a proper distance between vehicles

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High Level DesignPotential Fields Method (PFM)-Simple version of the Fuzzy Logic Controller-Vehicle is modeled as a particle in space, acted on by some combination of attractive and repulsive fields-Obstacles are modeled as charged surfaces-Net potential generates a desired velocity on the vehicle-Suitable for real-time motion planning of vehicle since the algorithm is simple-Widely used in obstacle avoidance applications for mobile robots, manipulators

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High Level Implementation

Host vehicle speed, relative speed and distance data measured by Encoder and RADAR sensor is processed with PFM algorithm. Output of the PFM algorithm is the desired speed for the host vehicle.

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High Level Implementation X_Safe

Minimum safe distance between host and target car

Metre (m)

Th

Constant Time Headway

Second (s)

V_Host

Velocity of the host (follower) car

Velocity (m/s)

d0

Minimum safe interdistance used in X_Safe calculation

Metre (m)

X_Safe_Tolerance

Tolerance distance for X_Safe required to track the vehicle in front

Metre (m)

X

Actual distance between host and target car (Measured from Radar)

Metre (m)

X_Stop

Critical distance to avoid collision

Metre (m)

Acceleration

Deceleration of the host car (Required for X_Sb calculation)

Acceleration (m/s2)

X_Sb

Distance the host car start braking

Metre (m)

V_Target

Velocity of the leading (target) car

Velocity (m/s)

V_Relative

Host car speed according to target car (Relative speed measured from Radar)

Velocity (m/s)

V_CC_Setpoint

The velocity that is adjusted when the ACC is opened (Cruise Control Setpoint velocity)

Velocity (m/s)

V_Desired

Output of the ACC Unit (Desired velocity applied to the host car)

Velocity (m/s)

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47


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High Level ImplementationCase 1: X ≤ X_Stop

Case 2: X > X_Stop and X < (X_Safe - X_Safe_Tolerans)

Case 3: X >= (X_Safe - X_Safe_Tolerans) and X <= (X_Safe + X_Safe_Tolerans)

Case 4: X > (X_Safe + X_Safe_Tolerans) ve X < X_Sb

Case 5: X ≥ X_Sb

(X X _ Safe X _ Safe _ Tolerans)( V _ Host V _ T arg et)V _ Desired V _ T arg et

X _ Sb (X _ Safe X _ Sa

)*(

fe _ Tolerans)

V _ Desired V _ Target

V _ Desired 0

V _ T arg et

X _ SafeV _ Desired X

(X _ Safe _ T X

ol_ St

eraop *

ns

X _ Stop)

V _ Desired V _ CC _Setpoint

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High Level Simulations and ResultsAccuracy of the code, written in python programming language, is tested in software environment MATLAB

High Level Simulations and ResultsScenario 1: V_Host = 7m/s, V_Target = 3m/s, V_CC_Setpoint = 7m/s, X_Safe = 12m, X_Sb = 26m

Scenario 2: V_Host = 5.5m/s, V_Target = 1m/s, V_CC_Setpoint = 5.5m/s, X_Safe = 10.5m, X_Sb = 25.5625m

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High Level InfrastructureRaspbian System• Raspbian is a free operating system

based on Debian optimized for the Raspberry Pi hardware

• Debian is Linux based operating system which is set of basic programs and utilities that make Rpi Run

• Provides more than pure Linux OS: Comes with over 35000 packages pre-compiled software bundled, optimized for best performance

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High Level InfrastructureRaspberry Pi (Rpi)• Credit card sized single board computer• Runs some versions of the Linux OS such as

Debian, Arch Linux ARM, Raspbian, Pidora and also non-Linux distributions as RISC OS.

• Supports Python, C, C++, Java, Perl and Ruby Programming Languages

-700 MHz Low Power ARM11 Processor-Open VG GPU support s Open GL ES 2.0-512 MB SDRAM-Boots from Micro SD card, runs a version of Linux OS-Operates at 5V DC supply-10/100 BaseT Ethernet Socket-HDMI for Video, Jack for Audio outputs-4xUSB 2.0 Connector-40 pin GPIO Connector-Camera Connector, Display Connector

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High Level InfrastructurePython• Python is a widely used general-

purpose, high-level programming language

• Design philosophy of language emphasizes code readability

• Syntax allows expressing concepts in fewer lines of code than other languages such as C++, Java

• Supports multiple programming paradigms, including object-oriented, imperative and functional programming

• Python shell is used for execution

An instance of Python shell

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Proposed Radar Perception Algorithm• Recall that the implemented Radar driver is capable of gathering

information of many objects in the environment.• What about roadside objects?

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• What can a Radar Sensor perceive? A Vehicle

Proposed Radar Perception Algorithm

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• What about roadside objects? A Vehicle


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• How to prevent this?• Answer: We ignore an object if it is out of range of a certain lateral position

A Vehicle


58

Proposed Radar Perception Algorithm• How do we know which object to act upon?• Overall Conclusion: An object having minimum longtitudunal position and within the lateral position

constraints should be considered.

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for (i = 0; i < OBJE_SAYISI; i++) { if (_ObjelerIslenmis[i].ObjLongPos !=0) { //Aracin cok saginda ve cok solundaki objeleri discard et. if (min > _ObjelerIslenmis[i].ObjLongPos) { min = _ObjelerIslenmis[i].ObjLongPos; min_obje_indeksi = i; } } } if(min_obje_indeksi != 0) { if((_ObjelerIslenmis[min_obje_indeksi].ObjLatPos > -1*(ARAC_GENISLIGI/2)) && (_ObjelerIslenmis[min_obje_indeksi].ObjLatPos < (ARAC_GENISLIGI/2))) { //Do nothing } else { min_obje_indeksi = 0; //ObjectIndex=0 ise onde obje yok anlamina gelir } }

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Display Unit• Display unit hardware: 4DPi-35 3.5” TFT Touchscreen• Display unit software:• Designed by using Adobe Fireworks, Coded with pygame Library for Python• Gets info via TCP Client (XML protocol)• Cruise “+” “-” Touch Buttons to Adjust Cruise Speed• Displays target vehicle distance, speed; host vehicle

speed; cruise status and setpoint speed.

(real photo with simulation variables)

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PCB Realization of the System

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PCB Realization of the System

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Conclusion Until now, literature review about speed control of a DC motor and adaptive cruise control, conventional cruise control and ACC (adaptive cruise control) design, system electronics design, system software implementation has been completed and the completed systems were tested.

In this ongoing project, we intend to use different control algorithm for the development of the high-level controller, retrofit the OSKAR vehicle and make improvements in low level control unit. Also, because of too much circuit in vehicle which causes mess, we are still developed a printed circuit board design.

To sum up, we have built a prototype of Engine Control Unit for an electric vehicle and we defend an opinion that if this system continues to be developed, it will be used among the intelligent vehicle technologies for avoiding the traffic accidents.

adaptive cruise controller module design for the electric vehicle oskar 1 project supervisors:...

Documents

acc system work

acc controlled vehicle

hall effect encoder

vehicle motor

sensors communication

highlevel design

desired velocity values

feedback sensor