Integrated braking control for electric vehicles with in-wheel propulsion and fully decoupled brake-by-wire system

This paper introduces a case study on the potential of new mechatronic chassis systems for battery electric vehicles, in this case a brake-by-wire (BBW) system and in-wheel propulsion on the rear axle combined with an integrated chassis control providing common safety features like anti-lock braking system (ABS), and enhanced functionalities, like torque blending. The presented controller was intended to also show the potential of continuous control strategies with regard to active safety, vehicle stability and driving comfort. Therefore, an integral sliding mode (ISM) and proportional integral (PI) control were used for wheel slip control (WSC) and benchmarked against each other and against classical used rule-based approach. The controller was realized in MatLab/Simulink and tested under real-time conditions in IPG CarMaker simulation environment for experimentally validated models of the target vehicle and its systems. The controller also contains robust observers for estimation of non-measurable vehicle states and parameters e.g., vehicle mass or road grade, which can have a significant influence on control performance and vehicle safety

Global Chassis Control System Using Suspension, Steering, and Braking Subsystems

A novel Global Chassis Control (GCC) system based on a multilayer architecture with three levels: top: decision layer, middle: control layer, and bottom: system layer is presented. The main contribution of this work is the development of a data-based classification and coordination algorithm, into a single control problem. Based on a clustering technique, the decision layer classifies the current driving condition. Afterwards, heuristic rules are used to coordinate the performance of the considered vehicle subsystems (suspension, steering, and braking) using local controllers hosted in the control layer. The control allocation system uses fuzzy logic controllers. The performance of the proposed GCC system was evaluated under different standard tests. Simulation results illustrate the effectiveness of the proposed system compared to an uncontrolled vehicle and a vehicle with a noncoordinated control. The proposed system decreases by 14% the braking distance in the hard braking test with respect to the uncontrolled vehicle, the roll and yaw movements are reduced by 10% and 12%, respectively, in the Double Line Change test, and the oscillations caused by load transfer are reduced by 7% in a cornering situation

Vehicle Dynamics Control for Rollover Prevention

Vehicle rollover accidents are a particularly dangerous form of road accident. Existing vehicle dynamics controllers primarily deal with yaw stability, and are of limited use for dealing with problems of roll instability. This thesis deals with the development of a new type of vehicle dynamics control system, capable of preventing rollover accidents caused by extreme maneuvering. A control strategy based on limitation of the roll angle while following a yaw rate reference is presented. Methods for rollover detection are investigated. A new computationally–efficient control allocation strategy based on convex optimization is used to map the controller commands to the individual braking forces, taking into account actuator constraints. Simulations show that the strategy is capable of preventing rollover of a commercial van during various standard test maneuvers

Stability Control of Electric Vehicles with In-wheel Motors

Recently, mostly due to global warming concerns and high oil prices, electric vehicles have attracted a great deal of interest as an elegant solution to environmental and energy problems. In addition to the fact that electric vehicles have no tailpipe emissions and are more efficient than internal combustion engine vehicles, they represent more versatile platforms on which to apply advanced motion control techniques, since motor torque and speed can be generated and controlled quickly and precisely. The chassis control systems developed today are distinguished by the way the individual subsystems work in order to provide vehicle stability and control. However, the optimum driving dynamics can only be achieved when the tire forces on all wheels and in all three directions can be influenced and controlled precisely. This level of control requires that the vehicle is equipped with various chassis control systems that are integrated and networked together. Drive-by-wire electric vehicles with in-wheel motors provide the ideal platform for developing the required control system in such a situation. The focus of this thesis is to develop effective control strategies to improve driving dynamics and safety based on the philosophy of individually monitoring and controlling the tire forces on each wheel. A two-passenger electric all-wheel-drive urban vehicle (AUTO21EV) with four direct-drive in-wheel motors and an active steering system is designed and developed in this work. Based on this platform, an advanced fuzzy slip control system, a genetic fuzzy yaw moment controller, an advanced torque vectoring controller, and a genetic fuzzy active steering controller are developed, and the performance and effectiveness of each is evaluated using some standard test maneuvers. Finally, these control systems are integrated with each other by taking advantage of the strengths of each chassis control system and by distributing the required control effort between the in-wheel motors and the active steering system. The performance and effectiveness of the integrated control approach is evaluated and compared to the individual stability control systems, again based on some predefined standard test maneuvers

Motion Dynamics Control of Electric Vehicles

In this chapter, I will explain the dynamics of electric vehicle and the support systems of drivers in detail, considering both structure and the function of the vehicle. Furthermore, the reliability is discussed. In car development and design that I have, car dynamic control system, turn ability, comfort, and safety must all be considered simultaneously. The safety and the comfort for the driver which are connected with various road surfaces and as well as the speed depend on the physical performance of the vehicle. In this chapter, we will explain the dynamics of the vehicle and the support system of the driver in detail, considering both the structure and function of the vehicle. In the design and development of car dynamic control system, turn ability, comfort, and safety must all be considered simultaneously. The safeness and comfort during a drive on various road surfaces and speed depend on the performance of these basic abilities of the vehicle

Mild Hybrid Electric Vehicles: Powertrain Optimization for Energy Consumption, Driveability and Vehicle Dynamics Enhancements

This thesis deals with the modeling, the design and the control of mild hybrid electric vehicles. The main goal is to develop accurate design tools and methodologies for preliminary system and component level analysis. Particular attention is devoted to the configuration in which an electric machine is mounted on the rear axle of a passenger car. The use of such a machine in parallel with the internal combustion engine allows one to exploit different functionalities that are able to reduce the overall fuel consumption of the vehicle. In addition, the indirect coupling between the thermal and the electric machine, realized through the road and not by means of mechanical couplers, together with the position of the latter in the overall vehicle chassis system, enables such an architecture to be efficient both from the energy recovery and the full electric driving point of view. Chapter 1 introduces the problem of fuel consumption and emissions reduction in the overall world context and presents the main hybrid architectures available. Chapter 2 is devoted to the study of the influence of the electric machine position in the powertrain regarding the regenerative braking potentialities concerned. The model considered for the analysis will be described on each of its subcomponents. The braking performance of the vehicle in electric mode is presented considering no losses in the electric powertrain (electric motor, battery, inverter). Chapter 3 is dedicated to the design of an electric machine for a rear axle powertrain. The specifications of such machine are optimized considering both the vehicle and the application under analysis. The design takes into account analytical techniques for the computation of electrical parameters (such as phase and DC currents) and the torque - speed map, as well as numerical ones for its thermal behavior. In Chapter 4 the electrical and thermal characteristics of the designed electric motor are implemented in the model presented in Chapter 2. The overall vehicle model is therefore used both to assess a simple torque split strategy between thermal and electric machine and to perform an optimal sizing of the battery considering all the limitations imposed by the electric powertrain (e. g. maximum currents, maximum temperatures). Chapter 5 makes a step forward and analyzes the different implications that the use of the rear axle electric motor to brake the vehicle has on the vehicle dynamics. Open loop analysis will present a degradation of the vehicle handling comfort caused by the introduction of an oversteering moment to the vehicle. Through the use of a simplified vehicle model, the introduced oversteering yaw moment is evaluated, while a control strategy based on a new stability detector will show how to find a trade off between handling comfort and regenerable energy. At last, Chapter 6 deals with the problem of longitudinal driving comfort. Drivelines and chassis are lightly damped systems and the application of an impulsive torque imposed by the driver can cause the vehicle longitudinal acceleration (directly perceived by the driver) to be oscillating and non smooth. A sensitivity analysis on a conventional powertrain is presented demonstrating which of the different components are more influential in the different modes of vibration, and possible solutions to improve the driveability are proposed. One of these relates to the use of the rear axle electric machine in order to give more responsiveness to the vehicle. Finally, concluding remarks are given in Chapter 7

Actuators for Intelligent Electric Vehicles

This book details the advanced actuators for IEVs and the control algorithm design. In the actuator design, the configuration four-wheel independent drive/steering electric vehicles is reviewed. An in-wheel two-speed AMT with selectable one-way clutch is designed for IEV. Considering uncertainties, the optimization design for the planetary gear train of IEV is conducted. An electric power steering system is designed for IEV. In addition, advanced control algorithms are proposed in favour of active safety improvement. A supervision mechanism is applied to the segment drift control of autonomous driving. Double super-resolution network is used to design the intelligent driving algorithm. Torque distribution control technology and four-wheel steering technology are utilized for path tracking and adaptive cruise control. To advance the control accuracy, advanced estimation algorithms are studied in this book. The tyre-road peak friction coefficient under full slip rate range is identified based on the normalized tyre model. The pressure of the electro-hydraulic brake system is estimated based on signal fusion. Besides, a multi-semantic driver behaviour recognition model of autonomous vehicles is designed using confidence fusion mechanism. Moreover, a mono-vision based lateral localization system of low-cost autonomous vehicles is proposed with deep learning curb detection. To sum up, the discussed advanced actuators, control and estimation algorithms are beneficial to the active safety improvement of IEVs

Model-Based Vehicle Dynamics Control for Active Safety

The functionality of modern automotive vehicles is becoming increasingly dependent on control systems. Active safety is an area in which control systems play a pivotal role. Currently, rule-based control algorithms are widespread throughout the automotive industry. In order to improve performance and reduce development time, model-based methods may be employed. The primary contribution of this thesis is the development of a vehicle dynamics controller for rollover mitigation. A central part of this work has been the investigation of control allocation methods, which are used to transform high-level controller commands to actuator inputs in the presence of numerous constraints. Quadratic programming is used to solve a static optimization problem in each sample. An investigation of the numerical methods used to solve such problems was carried out, leading to the development of a modified active set algorithm.Vehicle dynamics control systems typically require input from a number of supporting systems, including observers and estimation algorithms. A key parameter for virtually all VDC systems is the friction coefficient. Model-based friction estimation based on the physically-derived brush model is investigated

Trends in vehicle motion control for automated driving on public roads

In this paper, we describe how vehicle systems and the vehicle motion control are affected by automated driving on public roads. We describe the redundancy needed for a road vehicle to meet certain safety goals. The concept of system safety as well as system solutions to fault tolerant actuation of steering and braking and the associated fault tolerant power supply is described. Notably restriction of the operational domain in case of reduced capability of the driving automation system is discussed. Further we consider path tracking, state estimation of vehicle motion control required for automated driving as well as an example of a minimum risk manoeuver and redundant steering by means of differential braking. The steering by differential braking could offer heterogeneous or dissimilar redundancy that complements the redundancy of described fault tolerant steering systems for driving automation equipped vehicles. Finally, the important topic of verification of driving automation systems is addressed

직렬형 하이브리드 기반 6륜 인휠 차량의 최적 주행성, 안정성 및 에너지 효율을 위한 주행제어 알고리즘 개발

학위논문 (박사)-- 서울대학교 대학원 : 협동과정 자동차공학전공, 2012. 8. 이경수.본 논문은 직렬형 하이브리드 기반 6륜 인휠차량의 최적 주행성, 안정성 및 에너지 효율을 위한 주행제어 알고리즘 개발에 대하여 서술하였다. 대상 차량은 구동, 제동 및 조향이 독립적으로 가능한 시스템으로 구성되어 있다. 통합 주행제어 알고리즘은 6WD/6WS 차량의 최적 안정성, 주행성 및 에너지 효율을 위해 개발되었습니다. 제안된 알고리즘은 목표 동역학, 상위 제어, 하위 제어, 동력관리 계층을 포함하여 크게 4부분으로 구성되어 있습니다. 목표 동역학 계층은 운전자의 조향, 구동 및 제동 입력을 통해 각 휠의 조향각과 목표 속도 및 제동량을 결정합니다. 안정성 판단/제어, 요 모멘트 제어 및 속도 제어는 상위 제어기에 포함되어 있다. 안정성 판단/제어는 차량의 안정성을 판단하여 횡안정성 및 전복 안정성을 확보하기 위하여 G-vectoring과 요 모멘트 제어를 실시한다. 요 모멘트 제어는 요 안정성을 확보하기 위해 목표 요 속도를 만족시키는 목표 요 모멘트를 결정한다. G-vectoring 제어는 과도한 횡 가속도를 줄이기 위하여 종방향 가속도를 차량에 작용하게 하여 전복 안정성을 확보 하도록 설계하였다. 속도 제어는 운전자의 의도를 만족하기 위하여 슬라이딩 제어 기법을 기반으로 설계되었다. 하위 제어기는 각 휠의 슬립 상황, 인휠 모터의 토크 제한등을 고려하여 각 휠에 분배된다. 이를 위하여 Control Allocation 기법이 사용되었으며, 실시간 구현을 위하여 4가지 해석 기법을 개발하고 적용하여 적합한 알고리즘을 적용하였다. 동력관리 제어는 차량 구동에 있어서 연료소모량을 최소로 하기 위한 전략을 기반으로 설계되었다. 등가 연료 소모량 최소 전략 (ECMS)이 사용되어 최적의 연료 효율을 확보하였다. 제어기 성능 검증을 위하여 컴퓨터 시뮬레이션을 수행하였다. 시뮬레이션 결과를 통해 일반 차량의 성능과 비교하여, 크게 향상된 안정성, 주행성 및 에너지 효율을 확인 하였다.This paper describes an integrated driving control algorithm for optimized maneuverability and stability of a six-wheeled driving/brake and six-wheeled steering (6WD/6WS) electric combat vehicle which is equipped with drive/brake-by-wire and steer-by-wire modules. This integrated driving control algorithm is developed to obtain optimized stability, maneuverability and energy efficiency of a 6WD/6WS vehicle. The proposed control algorithm consists of four parts: desired dynamics, upper level control, lower level control and power management algorithm. The desired dynamics determines the steering angle of each wheel and the desired acceleration according to drivers steering, throttle, and braking inputs. Stability decision/control, yaw moment control, and speed control algorithms are included in the upper level control layer in order to track the desired dynamics and guarantee yaw and roll stability. The lower level control layer which is based on a control allocation method computes actuator commands, such as independent driving and regenerative braking torques. In the upper level control layer, the stability decision algorithm defines stability regions on a g-g diagram and calculates the desired longitudinal acceleration based on a G-vectoring control method and the desired yaw rate for lateral and yaw stability, and rollover prevention. The G-vectoring control algorithm determines the longitudinal acceleration required to keep the vehicle stable. The speed control calculates the desired longitudinal net force, and the desired net yaw moment is determined to track the desired yaw rate. Control allocation method is used to design the lower level control layer. Limitations related to the physical maximum output torque and prevention of excessive wheel slip are defined as control input constraints of control allocation, which takes friction circle information into account. For real-time implementation, four candidate methods have been designed and developed to solve the control allocation problem. Feasible method has been adopted, taking execution time into account in order to obtain optimized solutions. In the power management layer, from the determined input torque, the required power can be calculated. The required engine/generator and battery power are determined to minimize energy consumption. Fuel consumption minimization strategy (ECMS) is useful for on-line optimization and adopted to implement real-time applications. Computer simulations have been conducted to evaluate the proposed integrated driving control algorithm. It has been shown from simulation results that, compared to conventional drive systems, significantly improved vehicle maneuverability and stability can be obtained by the proposed integrated control algorithm.Abstract i List of Tables viii List of Figures ix Nomenclature xiii Chapter 1. Introduction 1 1.1 Background and Motivation 1 1.2 Previous Researches 3 1.2.1 Lateral Stability Control System 3 1.2.2 Torque Vectoring Control System 5 1.2.3 G-Vectoring Control System 7 1.2.4 Control Allocation 8 1.2.5 Power Management Control System 9 1.3 Thesis Objectives 11 1.4 Thesis Outline 13 Chapter 2. Control System Modeling 15 2.1 Control System Overview 15 2.2 Control System Architecture 18 2.3 Vehicle Dynamic, Actuators and Power System Model 20 2.3.1 Vehicle dynamic model 20 Body dynamics 21 Tire dynamics 22 2.3.2 Motor Dynamic model 24 2.3.3 Power System Model 25 2.3.4 Plannar Model for Control System Design 28 Stability analysis of the proposed 6WD/6WS platform 32 2.3.5 Bicycle model for Direct Yaw Moment Control Design 36 Chapter 3. Integrated Driving Control Algorithm 37 3.1 Desired Dynamics Layer 38 3.1.1 Desired steering angle determination 38 3.1.2 Desired velocity determination 40 3.2 Upper Level Control Layer 44 3.2.1 Stability decision algorithm 44 3.2.2 G-vectoring control algorithm 49 Accessibility of the G-vectoring control algorithm 50 Controllability of the G-vectoring control algorithm 53 Design of G-vectoring control algorithm 55 3.2.3 Yaw moment control algorithm 59 Performance verification based on frequency analysis 64 3.2.4 Speed control algorithm 70 Velocity tracking algorithm 71 Acceleration tracking algorithm 72 Switching algorithm 72 3.2.5 Stability analysis of the proposed control system 73 3.3 Lower Level Control Layer 79 3.3.1 Control Allocation Formulation 79 Cost function and constraints definition for control allocation problem formulation 81 Actuator Limitation Algorithm 91 Slip Limitation Algorithm 93 3.3.2 Fixed-point (FXP) control allocation method 97 3.3.3 Cascaded Generalized pseudo-inverse (CGI) method 99 3.3.4 Interior point (IP) method 101 3.3.5 Weighted least square method (WLS) 107 3.3.6 Implementation of control allocation 112 Unsaturated condition of control inputs 113 Saturated condition of control inputs 116 3.4 Power Management Layer 121 3.4.1 Equivalent fuel consumption minimization stratery(ECMS) 121 3.4.2 Design of engine/generator control algorithm 130 Chapter 4. Estimator Design 132 4.1 Longitudinal tire force estimation 133 4.2 Friction circle estimation 136 Chapter 5. Simulation Results 143 5.1 Turning Performance Verification – Open loop 151 5.2 Turning Performance Verification with Braking 156 5.3 Turning Performance Verification – Closed- loop 160 5.4 Lateral Stability Verification 162 5.5 Rollover Stability Verification 170 5.6 Driving Performance Verification for Gradient Road 173 5.7 Performance Verification of Energy Efficiency 175 5.8 Integrated Performance Verification using Test Track 186 5.9 Integrated Performance Verification using Test Track (DLC included) 195 Bibliography 202 국문초록 208Docto