Direct yaw moment control for electric vehicles with independent motors

Direct Yaw Moment Control (DYC) systems generate a corrective yaw moment to alter the vehicle dynamics by means of active distribution of the longitudinal tire forces, and they have been proven to be an effective means to enhance the vehicle handling and stability. The latest type of DYC systems employs the on-board electric motors of electric or hybrid vehicles to generate the corrective yaw moment, and it has presented itself as a more effective approach than the conventional DYC schemes. In this thesis, a wide range of existing vehicle dynamics control designs, especially the typical DYC solutions, are investigated. The theories and principles behind these control methods are summarized, and the features of each control scheme are highlighted. Then, a full vehicle model including the vehicle equivalent mechanical model, vehicle equations of motion, wheel equation of motion and Magic Formula tire model is established. Using the derived vehicle equations of motion, the fundamental mathematical relationships between the corrective yaw moment produced by the DYC system and the crucial vehicle states (the yaw rate and vehicle side-slip) are derived. Based on these relationships, two DYC systems are proposed for electric vehicles (or hybrid vehicles) by means of individual control of the independent driving motors. These two systems are designed to track the desired yaw rate and vehicle side-slip, respectively. Extensive simulation results verify that these systems are effective in improving vehicle dynamic performance. Apart from the two systems that adjust yaw rate or vehicle side-slip individually, a novel sliding mode DYC scheme is proposed to regulate both vehicle states simultaneously, aiming to better enhance the vehicle handling and stability. This control scheme guarantees the simultaneous convergences of both the yaw rate and vehicle side-slip errors to zero, and eliminates the limitations presented in the common sliding mode DYC solutions. Comparative simulation results indicate that the vehicle handling and stability are significantly enhanced with the proposed DYC system on-board. Also, this DYC scheme is shown to outperform its corresponding counterparts in various driving conditions

Optimal Direct Yaw Moment Control of a 4WD Electric Vehicle

This thesis is concerned with electronic stability of an all-wheel drive electric vehicle with independent motors mounted in each wheel. The additional controllability and speed permitted using independent motors can be exploited to improve the handling and stability of electric vehicles. In this thesis, these improvements arise from employing a direct yaw moment control (DYC) system that seeks to adapt the understeer gradient of the vehicle and achieve neutral steer by employing a supervisory controller and simultaneously tracking an ideal yaw rate and ideal sideslip angle. DYC enhances vehicle stability by generating a corrective yaw moment realized by a torque vectoring controller which generates an optimal torque distribution among the four wheels. The torque allocation at each instant is computed by finding a solution to an optimization problem using gradient descent, a well-known algorithm that seeks the minimum cost employing the gradient of the cost function. A cost function seeking to minimize excessive wheel slip is proposed as the basis of the optimization problem, while the constraints come from the physical limitations of the motors and friction limits between the tires and road. The DYC system requires information about the tire forces in real-time, so this study presents a framework for estimating the tire force in all three coordinate directions. The sideslip angle is also a crucial quantity that must be measured or estimated but is outside the scope of this study. A comparative analysis of three different formulations of sliding mode control used for computation of the corrective yaw moment and an evaluation of how successfully they achieve neutral steer is presented. IPG Automotive’s CarMaker software, a high-fidelity vehicle simulator, was used as the plant model. A custom electric powertrain model was developed to enable any CarMaker vehicle to be reconfigured for independent control of the motors. This custom powertrain, called TVC_OpenXWD uses the torque/speed map of a Protean Pd18 implemented with lookup tables for each of the four motors. The TVC_OpenXWD powertrain model and controller were designed in MATLAB and Simulink and exported as C code to run them as plug-ins in CarMaker. Simulations of some common maneuvers, including the J-turn, sinusoidal steer, skid pad, and mu-split, indicate that employing DYC can achieve neutral steer. Additionally, it simultaneously tracks the ideal yaw rate and sideslip angle, while maximizing the traction on each tire[CB1] . The control system performance is evaluated based on its ability to achieve neutral steer by means of tracking the reference yaw rate, stabilizing the vehicle by means of reducing the sideslip angle, and to reduce chattering. A comparative analysis of sliding mode control employing a conventional switching function (CSMC), modified switching function (MSMC), and PID control (HSMC) demonstrates that the MSMC outperforms the other two methods in addition to the open loop system

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

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

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

Optimization of a low weight electronic differential for LEVs

It is presented a performance analysis of an Electronic Differential (ED) system designed for Light Electric Vehicles (LEVs). We have developed a test tricycle vehicle with one front steering wheel and two rear fixed units is a same axis with a brushless DC integrated in each of them. Each motor has an independent controller unit and a common Arduino electronic CPU based that can plan specific speeds for each wheels as curves are being traced. Different implementations of sensors (input current/torque, steering angle and speed of the wheels) are discussed related to hardware complexity, and performance obtained based on speed level requirements and slipping on the traction wheels.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech