scholarly journals Energy Recovery Strategy Numerical Simulation for Dual Axle Drive Pure Electric Vehicle Based on Motor Loss Model and Big Data Calculation

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Huiyuan Xiong ◽  
Xionglai Zhu ◽  
Ronghui Zhang
Keyword(s):  
Numerical Simulation ◽  
Big Data ◽  
Feedback Control ◽  
Energy Recovery ◽  
Recovery Efficiency ◽  
Feedback Control System ◽  
Torque Distribution ◽  
Distribution Strategy ◽  
Braking Torque ◽  
Braking Force

Aiming at the braking energy feedback control in the optimal energy recovery of the two-motor dual-axis drive electric vehicle (EV), the efficiency numerical simulation model based on the permanent magnet synchronous motor loss was established. At the same time, under different speed and braking conditions, based on maximum recovery efficiency and data calculation of motor system, the optimization motor braking torque distribution model was established. Thus, the distribution rule of the power optimization for the front and rear electric mechanism was obtained. This paper takes the Economic Commission of Europe (ECE) braking safety regulation as the constraint condition, and finally, a new regenerative braking torque distribution strategy numerical simulation was developed. The simulation model of Simulink and CarSim was established based on the simulation object. The numerical simulation results show that under the proposed strategy, the average utilization efficiency of the motor system is increased by 3.24% compared with the I based braking force distribution strategy. Moreover, it is 9.95% higher than the maximum braking energy recovery strategy of the front axle. Finally, through the driving behavior of the driver obtained from the big data platform, we analyze how the automobile braking force matches with the driver’s driving behavior. It also analyzes how the automobile braking force matches the energy recovery efficiency. The research results in this paper provide a reference for the future calculation of braking force feedback control system based on big data of new energy vehicles. It also provides a reference for the modeling of brake feedback control system.

Intelligent optimization of EV comfort based on a cooperative braking system

2021 ◽  
pp. 095440702110044
Author(s):  
Lingying Zhao ◽  
Min Ye ◽  
Xinxin Xu
Keyword(s):  
System Model ◽  
Regenerative Braking ◽  
Coupling Mechanism ◽  
Intelligent Algorithm ◽  
Distribution Strategy ◽  
Braking System ◽  
Logic Diagram ◽  
Braking Torque ◽  
Braking Force ◽  
The Time Domain

To address the comfort of an electric vehicle, a coupling mechanism between mechanical friction braking and electric regenerative braking was studied. A cooperative braking system model was established, and comprehensive simulations and system optimizations were carried out. The performance of the cooperative braking system was analyzed. The distribution of the braking force was optimized by an intelligent method, and the distribution of a braking force logic diagram based on comfort was proposed. Using an intelligent algorithm, the braking force was distributed between the two braking systems and between the driving and driven axles. The experiment based on comfort was carried out. The results show that comfort after optimization is improved by 76.29% compared with that before optimization by comparing RMS value in the time domain. The reason is that the braking force distribution strategy based on the optimization takes into account the driver’s braking demand, the maximum braking torque of the motor, and the requirements of vehicle comfort, and makes full use of the braking torque of the motor. The error between simulation results and experimental results is 5.13%, which indicates that the braking force’s distribution strategy is feasible.

Optimization of Regenerative Braking Control Strategy for Pure Electric Vehicle

2017 ◽  
Vol 872 ◽  
pp. 331-336 ◽  
Author(s):  
Zhi Jun Guo ◽  
Dong Dong Yue ◽  
Jing Bo Wu
Keyword(s):  
Electric Vehicle ◽  
Control Strategy ◽  
Energy Recovery ◽  
Pso Algorithm ◽  
Regenerative Braking ◽  
Recovery Efficiency ◽  
Constraint Optimization ◽  
Vehicle Model ◽  
Braking Torque ◽  
Braking Control

The regenerative braking strategy for precursor pure electric vehicle was studied in this paper. Firstly, a constraint optimization model was established for the braking force distribution, in which both braking stability and recovery efficiency of braking energy were taken into account. Secondly, Particle Swarm Optimization (PSO) algorithm was applied to optimize the multi key parameters in the model. Finally, the optimized braking torque of the motor was obtained at different speed, different braking strength and different battery charge state. A vehicle model was built to validate the optimized results through simulation. The results showed that, compared with the original control strategy, the optimized control strategy not only could increase the braking stability effectively, but also improve the energy recovery efficiency in a certain extent.

scholarly journals Active torque distribution strategy for electric vehicle independent axle drive

2019 ◽  
Vol 100 ◽  
pp. 00037
Author(s):  
Artur Kopczyński
Keyword(s):  
Electric Vehicle ◽  
Electric Machines ◽  
Torque Distribution ◽  
Distribution Strategy ◽  
Braking Torque

Vehicles equipped with an electric independent axle drive have different properties compared to conventional vehicles. Distribution of driving or braking torque can be achieved by the proper control of the operation of electric machines without applying additional mechanisms. In this paper a method of active torque distribution between front and rear axles is presented. The method allows to use the maximum tyres adhesion and minimize slips. The results of simulation tests are presented, in which the active torque distribution with evenly torque distribution were compared.

scholarly journals A Control Algorithm for the Novel Regenerative–Mechanical Coupled Brake System with by-Wire Based on Multidisciplinary Design Optimization for an Electric Vehicle

Energies ◽  
2018 ◽  
Vol 11 (9) ◽  
pp. 2322 ◽  
Author(s):  
Changran He ◽  
Guoye Wang ◽  
Zhangpeng Gong ◽  
Zhichao Xing ◽  
Dongxin Xu
Keyword(s):  
Multidisciplinary Design Optimization ◽  
Control Algorithm ◽  
Multidisciplinary Design ◽  
Regenerative Braking ◽  
The Novel ◽  
Control Parameters ◽  
Torque Distribution ◽  
Distribution Strategy ◽  
Braking Torque ◽  
Sample Points

Current regenerative braking systems in electric vehicles have several problems, such as complex structures, too many control parameters, and inconsistent braking responses. To solve these problems, a control algorithm with multidisciplinary design optimization (MDO) is proposed based on the novel regenerative–mechanical coupled brake-by-wire system. A dynamic model of the novel regenerative braking system was established to analyze the mechanism of coupled braking and propose a braking torque distribution strategy. To realize a better balance between the optimum braking stability and the maximum regenerative energy recovery based on the braking torque distribution strategy and sample points, the MDO mathematical model was developed to optimize the control parameters with the collaborative optimization algorithm. The finite sample points comprising the vehicle speed, battery state-of-charge, and braking severity were obtained through an optimal Latin hypercube design and represent the overall design space. A network was established based on the sample points and the optimization results. Using this network, the in-depth characteristics of the sample points and the optimization results were obtained through supervised learning to develop the control algorithm for vehicle braking. A simulation was performed using the normal braking condition, and the simulation results demonstrated that the control algorithm has higher control precision than conventional methods and better real-time performance than online optimization.

Development of Parallel Regenerative Braking Controller

2011 ◽  
Vol 219-220 ◽  
pp. 1161-1164
Author(s):  
Jing Ming Zhang ◽  
Wei Nan Du ◽  
Xiu Hu Wang
Keyword(s):  
Energy Efficiency ◽  
Control Strategy ◽  
Energy Recovery ◽  
Regenerative Braking ◽  
Recovery Efficiency ◽  
Hardware In The Loop ◽  
Braking System ◽  
Driving Condition ◽  
Braking Force ◽  
Braking Control

In order to improve hybrid electric vehicle’s energy efficiency, this paper did a research on the regenerative braking system of HEV. In this paper we proposed a new parallel regenerative braking control strategy for HEV and analyzed its characteristics in details. Based on theoretical analysis, we developed a parallel regenerative braking controller for a certain HEV, and built hardware-in-the-loop simulation system to test the controller’s performance. We chose the UDDS driving condition for simulation, and the result shows that the regenerative braking controller we developed is effective and reliable. The controller fulfills the parallel regenerative braking control strategy and distributes the braking force accurately. The energy recovery efficiency reaches 16.7%, which significantly improves the vehicle’s energy efficiency.

scholarly journals Hierarchical Control Strategy for the Cooperative Braking System of Electric Vehicle

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Jiankun Peng ◽  
Hongwen He ◽  
Wei Liu ◽  
Hongqiang Guo
Keyword(s):  
Electric Vehicle ◽  
Control Strategy ◽  
Energy Recovery ◽  
Control Strategies ◽  
Hierarchical Control ◽  
Regenerative Braking ◽  
Recovery Efficiency ◽  
Braking System ◽  
Braking Torque ◽  
Braking Energy Recovery

This paper provides a hierarchical control strategy for cooperative braking system of an electric vehicle with separated driven axles. Two layers are defined: the top layer is used to optimize the braking stability based on two sliding mode control strategies, namely, the interaxle control mode and signal-axle control strategies; the interaxle control strategy generates the ideal braking force distribution in general braking condition, and the single-axle control strategy can ensure braking safety in emergency braking condition; the bottom layer is used to maximize the regenerative braking energy recovery efficiency with a reallocated braking torque strategy; the reallocated braking torque strategy can recovery braking energy as much as possible in the premise of meeting battery charging power. The simulation results show that the proposed hierarchical control strategy is reasonable and can adapt to different typical road surfaces and load cases; the vehicle braking stability and safety can be guaranteed; furthermore, the regenerative braking energy recovery efficiency can be improved.

scholarly journals Interval Type-2 Fuzzy Logic Anti-Lock Braking Control for Electric Vehicles under Complex Road Conditions

2021 ◽  
Vol 13 (20) ◽  
pp. 11531
Author(s):  
Linfeng Lv ◽  
Juncheng Wang ◽  
Jiangqi Long
Keyword(s):  
Fuzzy Logic ◽  
Energy Recovery ◽  
Fuzzy Inference ◽  
Slip Rate ◽  
Recovery Efficiency ◽  
Braking Torque ◽  
Braking Control ◽  
Interval Type ◽  
The Ideal

To simultaneously track the ideal slip rate and realize ideal energy recovery efficiency under different complex road conditions, an electro-hydraulic compound anti-lock braking system based on interval type-2 fuzzy logic control strategy and its corresponding braking torque allocation strategy have been developed for electric vehicles. The proposed interval type-2 fuzzy logic controller aims to calculate the ideal total braking torque by four steps, namely, fuzzification, fuzzy inference, type reduction, and defuzzification. The slip rate error and the change rate of slip rate error are utilized as inputs in the fuzzification, and then, the membership degree interval of fuzzy variables determined by the upper and lower membership functions is used to calculate the activation degree interval of different fuzzy rules in the fuzzy inference process, which enhances the anti-interference ability to external uncertainties and internal uncertainties. The braking torque allocation strategy is proposed to maintain the maximum energy recovery efficiency on the premise of safe braking. The software of MATLAB/Simulink is applied to simulate the process of anti-lock braking control under two complex road conditions. Simulation results corroborate the proposed interval type-2 fuzzy logic anti-lock braking control system can not only obtain better slip rate control effect and outstanding robustness but also achieve ideal regenerative braking energy recovery efficiency under both joint-μ and split-μ road surfaces.

Research on Coordination Control Strategy of Hydraulic Retarder and Friction Brake of Coach

2014 ◽  
Vol 1049-1050 ◽  
pp. 1009-1012
Author(s):  
Kui Yang Wang ◽  
Jin Hua Tang ◽  
Guo Qing Li
Keyword(s):  
Control Strategy ◽  
Force Distribution ◽  
Coordination Control ◽  
Loop Control ◽  
Distribution Strategy ◽  
Dynamic Coordination ◽  
Braking Torque ◽  
Braking Force ◽  
Hydraulic Retarder ◽  
Friction Brake

Based on the matching relationship between curve I of ideal braking force distribution and curve β of brake’s braking force distribution, the effect of hydraulic retarder on braking stability of coach is analysed, and the ideal braking force distribution strategy between hydraulic retarder and friction brake is put forward. The coordination control strategy of braking force between hydraulic retarder and friction brake is analyzed, and the dynamic coordination control strategy based on double closed-loop control structure and the coordination control algorithm with Anti-lock brake system (ABS) based on state machine are put forward. According to the above-mentioned coordination control strategy between hydraulic retarder and friction brake, the braking torque of hydraulic retarder can be made full use of and the degree of wear and heat load of friction brake can be greatly reduced in the premise of ensuring braking safety and comfort.

Sign in / Sign up

Export Citation Format

Share Document