Smart Traction Control Systems for Electric Vehicles Using Acoustic Road-type Estimation

The application of traction control systems (TCS) for electric vehicles (EV) has great potential due to easy implementation of torque control with direct-drive motors. However, the control system usually requires road-tire friction and slip-ratio values, which must be estimated. While it is not possible to obtain the first one directly, the estimation of latter value requires accurate measurements of chassis and wheel velocity. In addition, existing TCS structures are often designed without considering the robustness and energy efficiency of torque control. In this work, both problems are addressed with a smart TCS design having an integrated acoustic road-type estimation (ARTE) unit. This unit enables the road-type recognition and this information is used to retrieve the correct look-up table between friction coefficient and slip-ratio. The estimation of the friction coefficient helps the system to update the necessary input torque. The ARTE unit utilizes machine learning, mapping the acoustic feature inputs to road-type as output. In this study, three existing TCS for EVs are examined with and without the integrated ARTE unit. The results show significant performance improvement with ARTE, reducing the slip ratio by 75% while saving energy via reduction of applied torque and increasing the robustness of the TCS.Comment: Accepted to be published by IEEE Trans. on Intelligent Vehicles, 22 Jan 201

Application of Fuzzy control algorithms for electric vehicle antilock braking/traction control systems

Abstract—The application of fuzzy-based control strategies has recently gained enormous recognition as an approach for the rapid development of effective controllers for nonlinear time-variant systems. This paper describes the preliminary research and implementation of a fuzzy logic based controller to control the wheel slip for electric vehicle antilock braking systems (ABSs). As the dynamics of the braking systems are highly nonlinear and time variant, fuzzy control offers potential as an important tool for development of robust traction control. Simulation studies are employed to derive an initial rule base that is then tested on an experimental test facility representing the dynamics of a braking system. The test facility is composed of an induction machine load operating in the generating region. It is shown that the torque-slip characteristics of an induction motor provides a convenient platform for simulating a variety of tire/road - driving conditions, negating the initial requirement for skid-pan trials when developing algorithms. The fuzzy membership functions were subsequently refined by analysis of the data acquired from the test facility while simulating operation at a high coefficient of friction. The robustness of the fuzzy-logic slip regulator is further tested by applying the resulting controller over a wide range of operating conditions. The results indicate that ABS/traction control may substantially improve longitudinal performance and offer significant potential for optimal control of driven wheels, especially under icy conditions where classical ABS/traction control schemes are constrained to operate very conservatively

A state-of-the-art review on torque distribution strategies aimed at enhancing energy efficiency for fully electric vehicles with independently actuated drivetrains

© 2019, Levrotto and Bella. All rights reserved. Electric vehicles are the future of private passenger transportation. However, there are still several technological barriers that hinder the large scale adoption of electric vehicles. In particular, their limited autonomy motivates studies on methods for improving the energy efficiency of electric vehicles so as to make them more attractive to the market. This paper provides a concise review on the current state-of-the-art of torque distribution strategies aimed at enhancing energy efficiency for fully electric vehicles with independently actuated drivetrains (FEVIADs). Starting from the operating principles, which include the "control allocation" problem, the peculiarities of each proposed solution are illustrated. All the existing techniques are categorized based on a selection of parameters deemed relevant to provide a comprehensive overview and understanding of the topic. Finally, future concerns and research perspectives for FEVIAD are discussed

전륜 구동 차량의 핸들링 성능을 위한 전자식 차동 제한 장치의 예측 제어 전략

학위논문 (박사) -- 서울대학교 대학원 : 공과대학 기계항공공학부, 2020. 8. 이경수.This dissertation focused on a predictive control strategy for improved handling and acceleration performance of front-wheel-drive vehicles with electronic limited slip differential. Conventional front-wheel-drive cars have certain disadvantages, including a lack of accelerating performance and excessive understeer during acceleration in turn, due to the fact that spin of the inner driving wheel can occur with a small vertical load on the wheel. To address this problem, control logic is proposed for an electronic limited slip differential (ELSD) to enhance handling and acceleration performance. The proposed ELSD control algorithm consists of four parts. (1) Understeer prevention logic is developed for acceleration in turn. First, for a rapid response, the driving torque is distributed in advance to the inner and outer wheels according to the magnitude of the estimated traction potential in the wheels. If wheel spin occurs because of insufficient inner grip, then additional driving torque is transmitted to the outer wheel in proportion to the increment of the inner wheel speed compared to the outer wheel. However, the torque transfer to the outer wheel is limited in proportion to the excess speed of the outer wheel compared to the non-driving wheel to prevent power slides. (2) Oversteer prevention logic can reduce overshooting yaw motion during severe lane changes. The algorithm transmits driving torque from the outer wheel to the inner wheel in proportion to the level of excess yaw rate relative to the target yaw rate. (3) A cooperative control strategy with an electronic stability control (ESC) system is developed to decouple the ELSD/ESC system from the overlapped control timing. (4) Steering feel compensation logic is applied to the electric power-assist steering to prevent a torque steer effect caused by torque bias. The performance of the proposed algorithm has been investigated via vehicle tests. The proposed algorithm has been verified through patents on the control method and friction estimation approach for the novelty of this research. The ELSD with the proposed algorithm was then applied to mass production. This approach received positive feedback from international media due to the significant improvements in vehicle performance via ELSD. The system with the proposed algorithm also was won the IR52 Jang Young-shil Award for its technological importance, originality, economic value, and technical spill-over.논문은 전륜 구동 차량의 핸들링 및 가속 성능 향상을 위한 전자식 차동 제한 장치, Electronic Limited Slip Differential (ELSD)의 예측 제어 전략에 초점을 맞췄다. 기존 전륜 구동 차는 바퀴에 작은 수직하중으로 선회 내측 구동 휠의 스핀이 발생할 수 있기 때문에 선회 중 가속 시 가속 성능 면에서 불리하고 언더스티어가 과해지는 등 전형적인 단점이 있다. 이 문제를 해결하기 위해 ELSD에 대한 제어 로직을 제안하여 조종안정성 및 가속 성능을 향상시켰다. 제안된 전자식 차동제한장치 제어 알고리즘은 네 부분으로 구성된다. (1) 선회 중 가속 성능 향상을 위해 언더스티어 방지 로직을 제안하였다. 첫째, 빠른 응답을 위해 휠의 구동 가능 접지력 추정 값의 크기에 따라 선회 내측 및 외측 휠에 구동 토크를 미리 분배한다. 그래도 선회 내측 접지력이 부족하여 휠 스핀이 발생하는 경우, 외측 휠 속도 대비 내측 휠 속도의 초과량에 비례하여 추가 구동 토크를 외측 휠로 전달한다. 다만 외측 휠의 스핀은 절대로 허용하지 않기 위해 비구동 휠 속도 대비 구동 외측 휠 속도의 초과량에 비례하여 외측 휠로의 토크 전달을 제한한다. (2) 오버스티어 방지 로직은 심한 차선 변경 시 과한 요 거동을 안정화할 수 있다. 알고리즘은 목표 요 속도 대비 실제 차량의 요 속도 초과량에 비례하여 선회 외측 휠에서 내측 휠로 구동 토크를 전달한다. (3) Electronic Stability Control (ESC) 시스템과의 협조 제어 전략은 구동 토크와 제동 토크의 중복으로부터 ELSD/ESC 시스템을 분리하기 위해 제안되었다. (4) 조향 반력 토크 보상 제어 로직은 좌/우 구동 토크 차이로 인한 토크 스티어 효과를 방지하기 위해 전기식 파워 보조 조향 시스템에 보상 토크를 인가한다. 본 알고리즘은 차량 테스트를 통해 평가되었다. 제안된 알고리즘은 제어 방법과 마찰 추정 방법에 대한 특허를 통해 독창성을 검증 받았다. 그리고 제안된 알고리즘이 적용된 ELSD는 고성능 양산 차량에 적용되었다. 그 후, ELSD로 인해 차량 성능 크게 향상된 부분과 관련하여 국외 매체로부터 긍정적인 피드백을 받았다. 또한 제안된 알고리즘이 적용된 시스템은 IR52 장영실상을 수상하여, 기술적 중요성, 독창성, 경제적 가치, 기술적 파급력을 검증 받았다.Table of Contents Chapter 1. Introduction 1 1.1 Background and Motivation 1 1.2 Previous Researches 3 1.3 Thesis Objectives 10 1.4 Thesis Outline 16 Chapter 2. Analysis of Lateral Torque Transfer of Electronic Limited Slip Differential (ELSD) System 17 Chapter 3. Electronic Limited Slip Differential (ELSD) Handling Control Algorithm Overview 22 Chapter 4. Control Logic for Understeer Prevention 28 4.1 Wheel Spin Predictive Control 29 4.1.1 Model-based Predictive Control Overview 29 4.1.2 Allowable Driving Force Prediction Modeling 32 4.2 Wheel Speed Feedback Control 38 4.2.1 Control for Inner Wheel Spin Prevention 38 4.2.2 Control for Outer Wheel Spin Prevention 40 4.3 US Prevention Control General Summary 43 Chapter 5. Control Logic for Oversteer Prevention 50 5.1 Yaw Rate Feedback Control 51 Chapter 6. Integrated Control of Electronic Stability Control (ESC), Electric Power-assist Steering (EPS), and Electronic Limited Slip Differential (ELSD) 53 6.1 Cooperative Control with ESC 53 6.2 Cooperative Control with EPS 58 Chapter 7. Chapter 7 Tire-road Friction Estimation to Improve the Predictive Control 60 Chapter 8. Validation: Vehicle Tests 66 8.1 Configuration of Vehicle Tests 68 8.2 Closed-loop Acceleration in A Turn 73 8.3 Closed-loop Double Lane Change 80 8.4 Performance Comparison with Competitor 87 Chapter 9. Conclusions and Future Works 90 Bibliography 93 Abstract in Korean 96Docto

The effect of half-shaft torsion dynamics on the performance of a traction control system for electric vehicles

This article deals with the dynamic properties of individual wheel electric powertrains for fully electric vehicles, characterised by an in-board location of the motor and transmission, connected to the wheel through half-shafts. Such a layout is applicable to vehicles characterised by significant power and torque requirements where the adoption of in-wheel electric powertrains is not feasible because of packaging constraints. However, the dynamic performance of in-board electric powertrains, especially if adopted for anti-lock braking or traction control, can be affected by the torsional dynamics of the half-shafts. This article presents the dynamic analysis of in-board electric powertrains in both the time domain and the frequency domain. A feedback control system, incorporating state estimation through an extended Kalman filter, is implemented in order to compensate for the effect of the half-shaft dynamics. The effectiveness of the new controller is demonstrated through analysis of the improvement in the performance of the traction control system

Traction and Launch Control for a Rear-Wheel-Drive Parallel-Series Plug-In Hybrid Electric Vehicle

Hybrid vehicles are becoming the future of automobiles leading into the all-electric generation of vehicles. Electric vehicles come with a great increase in torque at lower RPM resulting in the issue of transferring this torque to the ground effectively. In this thesis, a method is presented for limiting wheel slip and targeting the ideal slip ratio for dry asphalt and low friction surfaces at every given time step. A launch control system is developed to further reduce wheel slip on initial acceleration from standstill furthering acceleration rates to sixty miles per hour. A MATLAB Simulink model was built of the powertrain as well as a six degree of freedom vehicle model that has been validated with real testing data from the car. This model was utilized to provide a reliable platform for optimizing control strategies without having to have access to the physical vehicle, thus reducing physical testing. A nine percent increase has been achieved by utilizing traction control and launch control for initial vehicle movement to sixty miles per hour

Adaptive Traction, Torque, and Power Control Strategies for Extended-Range Electric Vehicles

Modern hybrid electric and pure electric vehicles are highly dependent on control algorithms to provide seamless safe and reliable operation under any driving condition, regardless of driver behavior. Three unique and independently operating supervisory control algorithms are introduced to improve reliability and vehicle performance on a series-hybrid electric vehicle with an all-wheel drive all-electric drivetrain. All three algorithms dynamically control or limit the amount of torque that can be delivered to the wheels through an all-electric drivetrain, consisting of two independently controlled brushless-direct current (BLDC) electric machines. Each algorithm was developed and validated following a standard iterative engineering development process which places a heavy emphasis on modeling and simulation to validate the algorithms before they are tested on the physical system. A comparison of simulated and in-vehicle test results is presented, emphasizing the importance of modeling and simulation in the design process

Yaw Rate and Sideslip Angle Control Through Single Input Single Output Direct Yaw Moment Control

Electric vehicles with independently controlled drivetrains allow torque vectoring, which enhances active safety and handling qualities. This article proposes an approach for the concurrent control of yaw rate and sideslip angle based on a single-input single-output (SISO) yaw rate controller. With the SISO formulation, the reference yaw rate is first defined according to the vehicle handling requirements and is then corrected based on the actual sideslip angle. The sideslip angle contribution guarantees a prompt corrective action in critical situations such as incipient vehicle oversteer during limit cornering in low tire-road friction conditions. A design methodology in the frequency domain is discussed, including stability analysis based on the theory of switched linear systems. The performance of the control structure is assessed via: 1) phase-plane plots obtained with a nonlinear vehicle model; 2) simulations with an experimentally validated model, including multiple feedback control structures; and 3) experimental tests on an electric vehicle demonstrator along step steer maneuvers with purposely induced and controlled vehicle drift. Results show that the SISO controller allows constraining the sideslip angle within the predetermined thresholds and yields tire-road friction adaptation with all the considered feedback controllers

Electric Vehicle Efficient Power and Propulsion Systems

Vehicle electrification has been identified as one of the main technology trends in this second decade of the 21st century. Nearly 10% of global car sales in 2021 were electric, and this figure would be 50% by 2030 to reduce the oil import dependency and transport emissions in line with countries’ climate goals. This book addresses the efficient power and propulsion systems which cover essential topics for research and development on EVs, HEVs and fuel cell electric vehicles (FCEV), including: Energy storage systems (battery, fuel cell, supercapacitors, and their hybrid systems); Power electronics devices and converters; Electric machine drive control, optimization, and design; Energy system advanced management methods Primarily intended for professionals and advanced students who are working on EV/HEV/FCEV power and propulsion systems, this edited book surveys state of the art novel control/optimization techniques for different components, as well as for vehicle as a whole system. New readers may also find valuable information on the structure and methodologies in such an interdisciplinary field. Contributed by experienced authors from different research laboratory around the world, these 11 chapters provide balanced materials from theorical background to methodologies and practical implementation to deal with various issues of this challenging technology. This reprint encourages researchers working in this field to stay actualized on the latest developments on electric vehicle efficient power and propulsion systems, for road and rail, both manned and unmanned vehicles