Braking Of Electric Vehicle Research Articles

Adaptive Robust Control for Driving and Regenerative Braking of Electric Vehicle

The driving and braking energy recovery system of electric vehicle faces a lot of uncertainties, including the system parameters and the running environment uncertainties. An adaptive robust control (ARC) is presented in this paper to treat the problems including disturbance and parameter variation in the design of driving and regenerative braking controller. It can enhance the stability robustness and performance robustness. A model of the driving and regenerative braking system is constructed and then the ARC controller is designed. The experiment results show that the controller based on ARC theory has better performance of stability, robustness, and disturbance attenuation than traditional PID controller.

Development and Prospect of Regenerative Braking Technology of Electric Vehicles

The recovery of braking energy is an important characteristic of electric vehicles, and the technology of regenerative braking is one of the key technologies for electric vehicles. In this paper, after analyzing the main technical problems in regenerative braking of electric vehicles, the relevant research and development at home and abroad is introduced in detail, and its prospect of development is introduced at the end of this paper.

Evaluation Method of Regenerative Braking for Electric Vehicles

Regenerative braking is one of the key technologies to improve the energy efficiency of electric automobile, but there is no available scientific method to evaluate the effectiveness of regenerative braking for electric automobile. The paper research regenerative system conformation and control strategy .An efficiency evaluation index of regenerative braking system is introduced based on brake energy flow model.

Control allocation for regenerative braking of electric vehicles with an electric motor at the front axle using the state-dependent Riccati equation control technique

In this paper the systematic development of an integrated braking controller for a vehicle driven by an electric motor on the front axle is presented. The objective is to engage the electric motor only during braking, up to the point at which the vehicle reaches its manoeuvrability and stability limit. The control challenges are to distribute the braking effort correctly between the hydraulic brakes at the four tyres and the electric motor, to handle the tyre saturation and motor constraints effectively and to adapt the control allocation based on the vehicle’s states. The controller is designed using the state-dependent Riccati equation control technique, the vehicle state estimation and the ‘magic formula’ tyre model. The state-dependent Riccati equation control technique is a suboptimal control design technique for non-linear systems. A novel method for constructing the state-dependent coefficient formulation of the system dynamics is proposed. Soft constraints in the state dynamics are described, while an augmented penalty approach is suggested for handling the system’s hard constraints. The performance of the controller was evaluated for different braking scenarios using simulations in a MATLAB/Simulink environment. An eight-degree-of-freedom non-linear vehicle model was utilized. The numerical results show that the controller suboptimizes the regenerative braking effort while considering the tyre force saturation, the motor torque limits, the vehicle yaw rate and the slip angle error. A comparison with a constrained linear quadratic regulator shows the advantages of the proposed controller.

Concentrated Driving Electric Passenger Vehicle Braking Control Strategy Optimization

Regarding the centralized driving electric bus as the research object, the influence of Regenerative braking for vehicle braking performance is analyzed, and the original brake system was optimized, a braking control strategy, which does not reduce the vehicle braking safety and performance on the conditions of recovering braking energy as much as possible.

Energy recapture through deceleration – regenerative braking in electric vehicles from a user perspective

We report results from a 1-year field study (N = 80) on user interactions with regenerative braking in electric vehicles. Designed to recapture energy in vehicles with electric powertrains, regenerative braking has an important influence on both the task of driving and energy consumption. Results from user assessments and data from onboard data loggers indicate that most drivers quickly learned to interact with the system, which was triggered via accelerator. Further, conventional braking manoeuvres decreased significantly as the majority of deceleration episodes could only be executed through regenerative braking. Still, some drivers reported difficulties when adapting to the system. These difficulties could be addressed by offering different levels of regeneration so that the intensity of the deceleration could be individually modified. In general, the system is trusted and regarded as a valuable tool for prolonging range. Practitioner Summary: Regenerative braking in electric vehicles has direct implications for the driving task. We found that drivers quickly learn to use and accept a system, which is triggered via accelerator. For those reporting difficulties in the interaction, it appears reasonable to integrate options to customise or switch off the system.

Control Information and Data Processing of Vehicle based on Global Position System

A testing system based on Data Stream function of vehicle electronic control system was developed to test the city bus driving cycle. A mufti-function Vehicle Traveling Data Recorder based on GPS which can realize the vehicles positioning and navigating was investigated. The system included data acquisition module, display module, print module, GPS module, communication module and so on. This system adopts the FRAM memory as the storing equipment in which the automobile realized the real-time data store. It could realize the real-time data transmission of automobile and remote controlling by M22 GPRS module which includes TCP/IP. Optimizing of Muti-Energy power train control strategy was the key technical of Hybrid Electric Vehicle. Three kind structure of HEV and their control strategy were investigated, Series Hybrid Electric Vehicle, Parallel Hybrid Electric Vehicle, and PSHEV. Considering about driving cycle of CYC_NEDC and CYC_HWFET, three control strategies such as Electric Assistant Control, Simulation and experiment evaluation for regenerative braking of hybrid electric vehicle was investigated. The test result shows that the regenerative current in the road test and dynamometer test had little difference. The result shows that fuel consumption value got by the chassis dynamometer test evaluation method was closer to the value got by outdoor road test method.

Study on Control Strategy for Regenerative Braking of Electric Vehicles

To improve the efficiency of braking energy recovery,a control strategy for braking force distribution was designed.The front and rear wheels braking force were distributed according to the braking intensity,motor characteristics and relevant regulations.A simulation model was created and analyzed for this control strategy on the basis of software simulationX.The result shows that nearly 26% of total energy consumption are recovered effectively under the UDDS cycle on the premise of security and stability.

EBD Step-up Control Research during Cornering Braking for Electric Vehicles on High Energy Regenerative Braking/Driving Integrated System

This paper sets up high energy regenerative braking and driving integrated system for electric vehicle and its dynamic model based on the wheel hub motor and friction brake integrated into electric vehicle braking system. Bend EBD hierarchical strategy of control is put forward, which is based on ABS system. Establish dynamic simulation system of electric vehicle integrated brake system and EBD control simulation system based on the Matlab /Simulink. Based on CheryA3 model car, the wheel hub motor drive system replaces the power system; carry out simulation and analyze the control performance of the integrated braking system during cornering braking. The results show that the bend EBD control performance of high energy regenerative braking/driving integrated system for electric vehicle is good, which has a high braking energy recovery rate, braking efficiency and braking stability.

Integrated control of electromechanical braking and regenerative braking in plug-in hybrid electric vehicles

This paper proposes the use of Electromechanical Brakes (EMB) in combination with regenerative braking in PHEV so braking force can be distributed to front and rear axles according to an optimal curve instead of a linear line. Therefore, more braking force will be distributed to front axle, which will offer more kinetic energy for regenerative braking. Fuzzy logic control is used to allocate braking force between regenerative braking and electromechanical braking. The paper also studies antilock braking control of EMB to maintain safety and stability of a vehicle using sliding-mode control with switching gain fuzzy adjusting.

Design and implementation of automated regenerative braking of electric/hybrid electric vehicle

The hybrid electric vehicle (HEV) has become one of the most promising vehicles in the automobile industry due to its energy saving ability and low emission of harmful pollutants. An HEV can recover energy from the wheels, which had been wasted in the past, and reuse it to propel the vehicle at low speeds during high acceleration. The technology used depends on the goals set for the vehicle, which includes fuel efficiency, power, driving range, or reduced greenhouse gas emissions. The proposed project deals with the design, fabrication and testing of control logic circuit for regenerative braking of hybrid electric vehicle, by using multi–quadrant DC chopper (MQDC) with MOSFETs acting as switches. Monostable multi–vibrator is being used for firing the MOSFETs. The triggering for monostable multi–vibrator is provided by using the square wave generator. Micro–processor is interfaced with hardware circuit to show various modes of HEV. To realise this logic, a dedicated software programme has been developed in 'C' language.

Study on Control Strategy of Regenerative Braking in Electric Vehicles

Regenerative braking of electric vehicles can not only conserve energy, but also increase driving range. Regenerative braking control strategy formulate proportional relation of regenerative braking and mechanical braking, how to distribution regenerative braking and mechanical braking has become the key problem of raising regenerative braking energy[1]．This paper research on the distribution of braking force in the braking process, formulate mathematical models and put forward a new control strategy. The new control strategy is simulated and analyzed in the ADVISOR. Used new control strategy, the results indicate that fuel economy, emission and dynamic of simulation vehicle are improved.

Regenerative braking in electric vehicles with all-wheel drive

Given an all–wheel drive (AWD) electric vehicle, an energy optimal strategy for regenerative braking is presented as an extension to a known front wheel drive (FWD) only strategy. Different types of motors and their power capability are considered. The all–wheel drive and a front wheel drive setup are compared based on simulation of multiple driving cycles (NEDC, FTP75, SFTP, and NYCC). The presented analysis can be used for design of electric vehicles with all–wheel drive system (AWD).

Simulation Research on Neural Network Sliding Mode Control of Energy-Regenerative Braking of Electric Vehicle

To improve the energy-regenerative efficiency and robustness of electric vehicle (EV), a novel energy-regenerative controller was designed and applied to the charge current loop of the EV. The controller that combines neural network (NN) with traditional sliding mode controller (SMC) comprises a radial basis function NN (RBFNN) and a SMC. The RBFNN is used to adaptively adjust the switching gain of the SMC. The simulation model of the energy-regenerative system is built with MATLAB/SIMULINK, and the simulation results show that comparing with traditional SMC, the NNSMC has better performance at response speed, steady-state tracking error and resisting disturbance in energy-regenerative process. Additionally, it can recover more energy.

Application of Energy Storage Technologies for Electric Railway Vehicles—Examples with Hybrid Electric Railway Vehicles

AbstractRegenerative braking of railway electric vehicles is effective when other powering vehicles, in other words electrical load, exist near the regenerating train on the same electrified line. So, at early mornings and late nights, or in the low‐density district lines, regeneration cancellation phenomenon often occurs and the regenerative brake force cannot be operated in accordance with the commanded value. The new high‐performance energy storage devices tackle the issues of energy storage and reuse technologies for on‐ground and on‐vehicle situations. A hybrid energy source is one effective solution. In this paper, the effective use of regenerating braking and the expected electricity storage technology in future for further energy conservation in the electric railway field will be outlined, with actual examples. Copyright © 2010 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

Robust control for regenerative braking of battery electric vehicle

Regenerative braking is an effective way to extend the driving range of a battery electric vehicle (BEV). First, the electrical circuit and principle are depicted in detail. Then, the mathematical model is derived step by step, based on parameter perturbation. Combining the merits and defects of H2 optimal control and H∞ robust control, a robust H2/H∞ controller is put forward to guarantee both system performance and robust stability. To attenuate parameter perturbation and nonlinear uncertainty, the H∞ norm of the sensitive functions from the parameter perturbation of the electrical circuit to the control input is taken as the evaluating index of robustness, and the H2 norm of the transfer function from the external disturbance to the angular velocity of the motor as the index of linear quadratic Gaussian control. The agreement between the simulated and experimental results on BEV ‘XJTUEV-II’ validated the feasibility and effectiveness of regenerative braking and showed that the proposed scheme was endowed with good control performance. Furthermore, more energy is recovered, and by the proposed method, the driving range is improved 4% more than that by the traditional PI controller.

Traction and braking of hybrid electric vehicles using control allocation

This paper considers how a reusable motion control system can be designed to handle Hybrid Electric Vehicle (HEV) systems. The design considers simultaneously energy management and vehicle stability control, by distributing the task among available actuators. The suggested control system includes a control law for longitudinal, lateral, and yaw motion and a control distributor which distributes the desired control signals on the available actuators. The distribution among available actuators is designed by using constrained control allocation with mixed optimisation formulation, which gives a smooth blending among the available actuators. Simulations confirm that the proposed motion control system not only works as a traction, braking, and steering controller, it also works well as a vehicle stability controller.

Hardware in the Loop Simulation of Vehicle Stability Control using Regenerative Braking and Electro Hydraulic Brake for Hybrid Electric Vehicle

Abstract In this paper, hardware in the loop simulation(HILS) for a hybrid electric vehicle(HEV) braking performance is performed to investigate the vehicle stability control algorithm in the varying road surface condition. The vehicle stability control algorithm consists of the optimal braking torque distribution between the regenerative braking and the electro hydraulic braking. In addition to the optimal braking torque distribution, a sliding mode type wheel slip control algorithm is proposed to maintain the target slip ratio. The HILS system is composed of 4 wheel calipers and the electro hydraulic brake(EHB) module, and dynamic model of the HEV powertrain constructed by MATLAB Simulink is used as a software part. It is found from the HILS results that vehicle stability control algorithm using the regenerative braking, EHB and slip ratio control is able to provide the improved braking performance such as shorter braking distance, smaller error of the sideslip angle and yaw rate.

Energy Saving and Environmental Measures in Railway Technologies: Example with Hybrid Electric Railway Vehicles

AbstractThe electric railway system is the highest class of energy efficient transportation means. This is due to two important points: (i) low running resistance (including low energy losses) and (ii) energy regeneration in braking.Regenerative braking of railway electric vehicles is effective when the other powering ones, in other words electrical load, exist near the regenerating train on the same electrified line. So, early in the morning and at midnight, or in the low‐density district lines, regeneration cancellation phenomenon often occurs and the regenerative brake force cannot be operated in accordance with the recommended value. Newly appeared high‐performance energy storage devices press the issues of energy storage and reuse technologies on ground and on vehicles. Hybrid energy source is one effective solution. In this paper, as an example, we show our trolley and on‐board battery hybrid controlled tramcar, developed to reduce regeneration cancellation. With the trolley line collective power as well as charge and discharge power of the on‐board lithium ion rechargeable battery, the hybrid energy providing and regenerating technology is achieved. The running test results show a maximum regenerative ratio of 44%, which is top class value in an electric railway system. Copyright © 2007 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

Iterative Learning Control of Antilock Braking of Electric and Hybrid Vehicles

Hybrid electric vehicles (HEVs) use multiple sources of power for propulsion which provides great ease and flexibility to achieve advanced controllability and additional driving performance. In this paper, the electric motor in HEV and electric vehicle (EV) propulsion systems is used to achieve antilock braking performance without a conventional antilock braking system (ABS). The paper illustrates that the antilock braking of HEV can be easily achieved using iterative learning control for various road conditions. A vehicle model, a slip ratio model, and a vehicle speed observer were developed to control the antilock performance of HEV during braking. Through iterative learning process, the motor torque is optimized to keep the tire slip ratio corresponding to the peak traction coefficient during braking. Simulations were performed on a compact size vehicle to validate the proposed control method. The control algorithm proposed in this paper may also be used for the ABS control of conventional vehicles.