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Volume 42 Issue 1
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Journal of Beijing University of Aeronautics and Astronautics  > 2016  >  42(1): 21-27.
JI Fenzhu, DU Farong, ZHU Wenboet al. Electric vehicle energy economy based on braking intention identification[J]. Journal of Beijing University of Aeronautics and Astronautics, 2016, 42(1): 21-27. doi: 10.13700/j.bh.1001-5965.2015.0031(in Chinese)
Citation: JI Fenzhu, DU Farong, ZHU Wenboet al. Electric vehicle energy economy based on braking intention identification[J]. Journal of Beijing University of Aeronautics and Astronautics, 2016, 42(1): 21-27. doi: 10.13700/j.bh.1001-5965.2015.0031(in Chinese)
shu

Electric vehicle energy economy based on braking intention identification

doi: 10.13700/j.bh.1001-5965.2015.0031
  • 1.

    School of Transportation Science and Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100083, China

  • 2. School of Energy and Power Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100083, China

Funds:  National High-tech Research and Development Program of China (2012AA111202); Beijing Natural Science Foundation (3122024)
  • Received Date: 16 Jan 2015
  • Publish Date: 20 Jan 2016
    Abstract
  • Braking energy recovery is a main technology measure for improving the energy economy of the electric vehicle. It is a key point to accurately identify the driving intent for braking energy recovery. The models of braking intention identification for lifting up the accelerating pedal and depressing the braking pedal were respectively established. Braking intention was identified using fuzzy control method. The identification results of driver braking intention were expressed as small-strength brake, middle-strength brake and emergency brake.Two types of energy recovery modes were made up based on the braking intention identification results. The braking force allocation strategy and calculation model were set up based on the economic commission of Europe (ECE) regulations line and I curve. A braking system simulation model was founded in the plate of Cruise and MATLAB/Simulink, and braking energy recovery rate and driving range of the electric vehicle were calculated for different energy recovery modes.The results show that: if energy recovery mode is different, the braking energy recovery rate is different; in a new European driving cycle (NEDC), the energy recovery rate could be improved in the case of recovering the braking energy in the stage of lifting up the accelerating pedal, and this braking energy is set to simulate engine braking in orthodox vehicle; the driving range increased 5.69% in NEDC.

     

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    • References(15)
  • [1]
    GAO Y,CHEN L,EHSANI M.Investigation of the effectiveness of regenerative braking for EV and HEV[C]//Proceedings of Future Transportation Technology Conference and Exposition.Costa Mesa,CA:SAE International,1999:2910-2916.
    [2]
    张俊智,陆欣,张鹏君,等.混合动力城市客车制动能量回收系统道路试验[J].机械工程学报,2009,45(2):25-30. ZHANG J Z,LU X,ZHANG P J,et al.Road test of hybrid electric bus with regenerative braking system[J].Journal of Mechanical Engineering,2009,45(2):25-30(in Chinese).
    [3]
    詹迅.轻度混合动力汽车再生制动系统建模与仿真[D].重庆:重庆大学,2005:5-9(in Chinese). ZHAN X.The modeling and simulation of regenerative braking system for mild hybrid electric vehicle[D].Chongqing:Chongqing University,2005:5-9(in Chinese).
    [4]
    OHKUBO N,MATSUSHITA S,UENO M,et al.Application of electric servo brake system to plug-in hybrid vehicle[J].SAE International Journal of Passenger Cars-electronic and Electrical Systems,2013,6(1):255-260.
    [5]
    FEN Z J,XIAO X Z,WEN B Z.Coordinate control of electro-hydraulic hybrid brake of electric vehicles based on Carsim[J].Applied Mechanics and Materials,2014,490-491:1120-1125.
    [6]
    POURSAMAD A,MONTAZERI M.Design of genetic-fuzzy control strategy for parallel hybrid electric vehicles[J].Control Engineering Practice,2008,16(7):861-873.
    [7]
    宋百玲,周学升.基于制动意图模糊识别的电动汽车再生制动研究[J].森林工程,2014,30(6):71-74. SONG B L,ZHOU X S.Research on regenerative braking system for electric vehicle based on braking intention fuzzy identification method[J].Forest Engineering,2014,30(6):71-74(in Chinese).
    [8]
    王庆年,孙磊,唐先智.HEV制动意图识别的研究[J].汽车工程,2013,35(9):769-774. WANG Q N,SUN L,TANG X Z.A study on braking intention identification for HEV[J].Automotive Engineering,2013,35(9):769-774(in Chinese).
    [9]
    初亮,王彦波,姚亮.制动能量回收系统的制动力矩协调控制仿真[J].华南理工大学学报(自然科学版),2014,42(4):137-142. CHU L,WANG Y B,YAO L,et al.Simulation of coordinated control of braking torque for braking energy recovery system[J].Journal of South China University of Technology(Natural Science Edition),2014,42(4):137-142(in Chinese).
    [10]
    付甜甜.绿色动力——之诺1E[J].电源技术,2014,38(9):1601-1602. FU T T.Green power-ZINORO 1E[J].Chinese Journal of Power Sources,2014,38(9):1601-1602(in Chinese).
    [11]
    马其贞.基于制动意图识别的制动能量回收控制算法研究[D].吉林:吉林大学,2013:17-29. MA Q Z.Study on regenerative brake control algorithm based on braking intention identification[D].Jilin:Jilin University,2013:17-29(in Chinese).
    [12]
    王庆年,王俊,陈慧勇,等.混合动力车辆中的加速与制动意图识别[J].吉林大学学报(工学版),2014,44(2):281-286. WANG Q N,WANG J,CHEN H Y,et al.Accelerating and braking intention identification in hybrid vehicle[J].Journal of Jilin University(Engineering and Technology Edition),2014,44(2):281-286(in Chinese).
    [13]
    刘丽君,姬芬竹,杨世春,等.基于ECE法规和I曲线的机电复合制动控制策略[J].北京航空航天大学学报,2013,39(1):138-142. LIU L J,JI F Z, YANG S C,et al.Control strategy for electromechanical braking based on curves of ECE regulations and ideal braking force[J].Journal of Beijing University of Aeronautics and Astronautics,2013,39(1):138-142(in Chinese).
    [14]
    YANG S C,ZHAO Q,TANG T Q.Modeling electric vehicle's following behavior and numerical tests[J].Journal of Central South University,2014,21:4378-4385.
    [15]
    李红.混合动力四驱汽车机电复合制动系统的研究[D].广州:华南理工大学,2014:29-33. LI H.Study on the mechanical and electrical braking system of 4WD hybrid electric vehicle[D].Guangzhou:South China University of Technology,2014:29-33(in Chinese).
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