Regenerative braking is an effective approach for electric vehicles (EVs) to extend their driving range. A fuzzy-logic-based regenerative braking strategy (RBS) integrated with series regenerative braking is developed in this paper to advance the level of energy-savings. From the viewpoint of securing car stability in braking operations, the braking force distribution between the front and rear wheels so as to accord with the ideal distribution curve are considered to prevent vehicles from experiencing wheel lock and slip phenomena during braking. Then, a fuzzy RBS using the driver's braking force command, vehicle speed, battery SOC, battery temperature are designed to determine the distribution between friction braking force and regenerative braking force to improve the energy recuperation efficiency. The experimental results on an "LF620" prototype EV validated the feasibility and effectiveness of regenerative braking and showed that the proposed fuzzy RBS was endowed with good control performance. The maximum driving range of LF620 EV was improved by 25.7% compared with non-RBS conditions.

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An Intelligent Regenerative Braking Strategy for Electric Vehicles

A control system by means of the back electromotive force method is designed for the position-sensorless electric vehicle (EV) after analyzing the principle of position-sensorless control for brushless dc motor. Aiming at the main problems of EV: variation of model and short driving range, a fuzzy sliding-mode controller (FSMC) with regeneration is designed for the EV. The controller uses fuzzy switching gain adjustment to avoid the whippings. The experimental results show that the control system of position-sensorless EV can successfully achieve position-sensorless commutation control and replace Hall sensors. FSMC possesses better performance and higher efficiency than the proportional-integral-differential controller. Additionally, it can recover more energy and increase more driving range.

Fuzzy-Logic-Based Sliding-Mode Controller Design for Position-Sensorless Electric Vehicle

The limitation of driving range is the key restriction for the development of EV (electric vehicle), and regenerative braking is an effective approach to extend the driving range of electric vehicle. To protect the battery from broken caused by large charging current during regenerative braking, the control strategy that makes the charging current as control object is proposed in this paper. To ensure the robustness of the closed-loop system under the presence of uncertainties, such as parameter perturbation and unknown model dynamics, and to minimize the effect of disturbance, such as the variation of the voltage of battery, state of the road, and the driving profile of vehicle, the design of controllers for regenerative braking is transformed into the weighted mixed-sensitivity problem, and the H infin robust controller for regenerative braking is designed. Finally, experimental researches on XJTUEV-1 under different driving modes are performed. The experimental results show that Hinfin robust controller is prior to the traditional PI controller in both steady-state tracking error and the key restriction for the development of EV (electric vehicle), and regenerative braking is an effective approach to extend the driving range of electric vehicle. To protect the battery from broken caused by large charging current during regenerative braking, the control strategy that makes the charging current as control object is proposed in this paper. To ensure the robustness of the closed-loop system under the presence of uncertainties, such as parameter perturbation and unknown model dynamics, and to minimize the effect of disturbance, such as the variation of the voltage of battery, state of the road, and the driving profile of vehicle, the design of controllers for regenerative braking is transformed into the weighted mixed-sensitivity problem, and the H infin robust controller for regenerative braking is designed. Finally, experimental researches on XJTUEV-I under different driving modes are performed. The experimental results show that Hinfin robust controller is prior to the traditional PI controller in both steady-state tracking error and response speed. Additionally the Hinfin robust controller for regenerative braking can recover more energy than PI controller during the EV braking

Research on control for regenerative braking of electric vehicle

A vehicle power controller for a vehicle including a motor that drives the vehicle, a plurality of sensors and a motor controller, wherein the plurality of sensors includes an accelerator sensor for sensing a position of an accelerator pedal and a brake sensor for sensing a position of a brake pedal, and wherein the motor controller controls torque output of the motor. The vehicle power controller includes three components. The first receives signals from the accelerator sensor and the brake sensor. The second converts the signals for the accelerator sensor and the brake sensor into a torque value, and the third outputs the torque value to the motor controller for controlling the torque output of the motor.

Electric vehicle chassis controller

This paper presents a regenerative anti-lock braking system control method with road detection capability. The aim of the proposed methodology is to improve electric vehicle safety and energy economy during braking maneuvers. Vehicle body longitudinal deceleration is used to estimate a road surface. Based on the estimation results, the controller generates an appropriate braking torque to keep an optimal for various road surfaces wheel slip and to regenerate for a given motor the maximum possible amount of energy during vehicle deceleration. A fuzzy logic controller is applied to fulfill the task. The control method is tested on a four in-wheel-motor drive sport utility electric vehicle model. The model is constructed and parametrized according to the specifications provided by the vehicle manufacturer. The simulation results conducted on different road surfaces, including dry, wet and icy, are introduced.

Design of Regenerative Anti-Lock Braking System Controller for 4 In-Wheel-Motor Drive Electric Vehicle with Road Surface Estimation

It is shown that, by exploiting the inherent tolerances in the braking system, a fuzzy controller can be used to achieve a more comfortable ride for the electric vehicle operator. Tolerances in energy recovery were exploited to gain a more acceptable performance. The fuzzy controller model reduces the velocity error but does not eliminate it completely. The magnitude of the errors has been reduced and separated to the two conditions where only one of the models is operating and the other either has not initiated deceleration or has turned off before the controller expected. These errors are due to the time variables of temperature, brake pad wear, brake pad temperature, and the mechanical frictions in the system. By using the tolerances available in both the energy recovery system and the operating conditions, smoother operation of the vehicle is possible. >

J. Paterson

Papers

Electric vehicle braking by fuzzy logic control