State and parameter estimation based on a modified particle filter for an in-wheel-motor-drive electric vehicle

被引：47

作者：

Zhu, Junjun ^{[1
,2
]}

Wang, Zhenpo ^{[1
,2
]}

Zhang, Lei ^{[1
,2
]}

Zhang, Wenliang ^{[1
,2
]}

机构：

[1] Beijing Inst Technol, Collaborat Innovat Ctr Elect Vehicles Beijing, Beijing 100081, Peoples R China

[2] Beijing Inst Technol, Natl Engn Lab Elect Vehicles, Beijing 100081, Peoples R China

来源：

MECHANISM AND MACHINE THEORY | 2019年 / 133卷

关键词：

In-wheel-motor-drive electric vehicle; State and parameter estimation; Genetic algorithm; Modified particle filter; IDENTIFICATION; TRANSMISSION; OBSERVER; DESIGN;

D O I：

10.1016/j.mechmachtheory.2018.12.008

中图分类号：

TH [机械、仪表工业];

学科分类号：

0802 ;

摘要：

This paper presents a modified particle filter (MPF) to estimate vehicle states and parameter with high precision and robustness under complex noises and sensor fault conditions. To deal with the particle impoverishment issue, the vector particle swarm of the multivariable system is separated into univariate particle swarms, which are diversified with the selection, crossover and mutation operations of the genetic algorithm (GA) while maintaining the mean value and enlarging the standard deviation. The effectiveness of the proposed estimation scheme is verified under the scenarios of the stochastic and needling noises and acceleration sensor faults through the Carmaker-Simulink joint simulations based on typical maneuvers, outperforming the commonly-used vehicle state estimators including the unscented Kalman filter (UKF) and the unscented particle filter (UPF). (C) 2018 Elsevier Ltd. All rights reserved.

引用

页码：606 / 624

页数：19

共 26 条

[11] A novel H∞ and EKF joint estimation method for determining the center of gravity position of electric vehicles [J].

Lin, Cheng ;

Gong, Xinle ;

Xiong, Rui ;

Cheng, Xingqun .

APPLIED ENERGY, 2017, 194 :609-616

[12] Lateral Stability Control of In-Wheel-Motor-Driven Electric Vehicles Based on Sideslip Angle Estimation Using Lateral Tire Force Sensors [J].

Nam, Kanghyun ;

Fujimoto, Hiroshi ;

Hori, Yoichi .

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2012, 61 (05) :1972-1985

[13] Design and evaluation of sideslip angle observer for vehicle stability control [J].

Pi, D. W. ;

Chen, N. ;

Wang, J. X. ;

Zhang, B. J. .

INTERNATIONAL JOURNAL OF AUTOMOTIVE TECHNOLOGY, 2011, 12 (03) :391-399

[14] Kalman filter-based integration of DGPS and vehicle sensors for localization [J].

Rezaei, Shahram ;

Sengupta, Raja .

IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, 2007, 15 (06) :1080-1088

[15]

Sabbioni E., 2015011510 SAE, DOI [10.4271/2015-01-1510, DOI 10.4271/2015-01-1510]

[16] Vehicle state estimation based on IEKF-APF [J].

Shen, Fapeng ;

Zhao, Youqun ;

Sun, Qiuyun ;

Lin, Fen ;

Wang, Wei .

Jixie Gongcheng Xuebao/Journal of Mechanical Engineering, 2014, 50 (22) :136-141

[17]

Syed U., 2016011654 SAE, DOI [10.4271/2016-01-1654, DOI 10.4271/2016-01-1654]

[18] Robust online roll dynamics identification of a vehicle using sliding mode concepts [J].

Tafner, Robert ;

Reichhartinger, Markus ;

Horn, Martin .

CONTROL ENGINEERING PRACTICE, 2014, 29 :235-246

[19] Sensor Fusion Based on an Integrated Neural Network and Probability Density Function (PDF) Dual Kalman Filter for On-Line Estimation of Vehicle Parameters and States [J].

Vargas-Melendez, Leandro ;

Boada, Beatriz L. ;

Boada, Maria Jesus L. ;

Gauchia, Antonio ;

Diaz, Vicente .

SENSORS, 2017, 17 (05)

[20] Cyber-Physical Control for Energy Management of Off-Road Vehicles With Hybrid Energy Storage Systems [J].

Wang, Hong ;

Huang, Yanjun ;

Khajepour, Amir .

IEEE-ASME TRANSACTIONS ON MECHATRONICS, 2018, 23 (06) :2609-2618

← 1 2 3 →