电动客车AMT换挡执行机构状态估计及参数辨识

doi:10.19562/j.chinasae.qcgc.2022.08.013

Abstract

Abstract:

In order to improve the shifting performance when the parameters of the automatic transmission shifting actuator are time-varying， a hierarchical state estimation and parameter identification method based on the nonlinear $H ∞$ algorithm is proposed， considering both the highly nonlinear system model and the unknown system noise characteristics. Firstly， the problem of time-varying parameters of the shifting actuator is found through experiments， and a nonlinear model is established for the shifting actuator. Then， the hierarchical state estimation layer and parameter identification layer are designed， both of which are based on the nonlinear $H ∞$ algorithm. The upper estimation layer estimates the state of the actuator and transfers the result to the lower identification layer； the lower identification layer applies the state results as the measurement， and uses the system model as the measurement equation to identify the system parameters. Then， the cooperative operation of the two layers estimate the state of the shifting actuator， and identifies the structural and electrical performance parameters. Finally， a state estimation and parameter identification process based on automatic calibration is designed， which realizes the parameter identification of the shift actuator while calibrating and correcting the shift position value. The test results show that the hierarchical state estimation and parameter identification method proposed in this paper can accurately estimate and identify the state and parameters of the shifting actuator. After modifying the parameters， the shifting performance of the system is improved.

Key words: automatic transmission, shifting actuator, state estimation, parameter identification

Cheng Lin,Jiang Yi,Yu Tian. State Estimation and Parameter Identification of Shifting Actuator of Automatic Transmission of Electric Vehicles[J].Automotive Engineering, 2022, 44(8): 1237-1250.

Figures/Tables 20

部件	项目	参数	备注
直流电机	电压平台	27 V
	空载电流	2 A	该电流为最大空载电流
	空载转速	3 900 r·min^-1 $±$ 10%
	0.9 N·m负载电流	22 A	该电流为 0.9 N·m负载最大电流
	0.9 N·m负载转速	2 100 r·min^-1 $±$ 10%
	1.55 N·m堵转电流	38 A	该电流为 1.55 N·m负载最大电流
	电磁转矩系数	0.055 7
	反电势系数	0.055 7
	电枢电阻	0.632 $Ω$
	电枢电感	0.005 H
	空载阻力矩	0.111 N·m
	转子转动惯量	0.000 1 kg·m²
换挡机构	$L a$	35 mm	丝杠到换挡指旋转轴的垂直距离
	$L b$	35 mm	换挡指力臂的最大值
	丝杠转动惯量	0.000 513 267 kg·m²
	螺母质量	0.032 02 kg
	换挡指惯量	0.001 158 416 kg·m²
	丝杠进给效率	0.9

References 26

1	刘志超，郑天雷，龚慧明，等. 基于中国工况的纯电动乘用车续驶里程评价方法研究［J］. 汽车工程， 2021， 43（5）： 705-712.
	LIU Zhichao， ZHENG Tianlei， GONG Huiming， et al. Research on evaluation method of driving range of battery electric passenger vehicle based on china automotive test cycle［J］. Automotive Engineering， 2021， 43（5）： 705-712.
2	郭景华，李文昌，王靖瑶，等. 智能电动汽车自适应巡航与再生制动多目标协同控制［J］. 汽车工程， 2020， 42（12）： 1638-1646.
	GUO Jinghua， LI Wenchang， WANG Jingyao， et al. Multi-objective integrated adaptive cruise and regenerative braking control of intelligent electric vehicles［J］. Automotive Engineering， 2020， 42（12）： 1638-1646.
3	万钢. 《新能源汽车产业发展规划（2021-2035年）》为新能源汽车产业发展制定路线［J］. 变频器世界， 2020（4）： 27-28.
	WAN G. The "New Energy Vehicle Industry Development Plan （2021-2035）" sets out a route for the development of the new energy vehicle industry ［J］. The World of Inverters， 2020 （4）： 27-28.
4	国务院办公厅. 新能源汽车产业发展规划（2021-2035年）［EB/OL］. 2020-11-02. http：//www.gov.cn/zhengce/content/2020-11/02/content_5556716.htm.
	General Office of the State Council of the People's Republic of China. New energy vehicle industry development plan （2021-2035）［EB/OL］. 2020-11-02. http：//www.gov.cn/zhengce/content/2020-11/02/content_5556716.htm.
5	林程. 北理工电动客车及奥运电动客车研发介绍［J］. 商用汽车， 2007（12）： 48-51.
	LIN C. Introduction of Beijing Institute of Technology electric bus and Olympic electric bus research and development ［J］. Commercial Vehicle Magazine， 2007 （12）： 48-51.
6	林歆悠，伍家鋆，魏申申. 双电机耦合驱动电动汽车驱动模式划分与优化［J］. 汽车工程， 2020， 42（4）： 425-430.
	LIN Xinyou， WU Jiayun， WEI Shenshen. Division and optimization of driving modes of electric vehicles with dual-motor coupling-propulsion powertrain［J］. Automotive Engineering， 2020， 42（4）： 425-430.
7	赵明杰. 双电机耦合变速驱动系统控制策略及换挡机理研究［D］. 北京：北京理工大学， 2021.
	ZHAO M J. Research on optimal control strategy and shifting mechanism for dual-motor-transmission coupling propulsion system ［D］. Beijing： Beijing Institute of Technology， 2021.
8	程一帆，李雪松，高炳钊，等.基于显式控制律设计的AMT电控系统开发流程与验证［J］.汽车工程，2021，43（5）：762-769.
	CHENG Yifan， LI Xuesong， GAO Bingzhao， et al. Development procedure and verification of AMT electrical control system based on explicit control law design［J］. Automotive Engineering， 2021，43（5）：762-769.
9	TIAN Feng， SUI Liqi， ZENG Yuanfan， et al. Hardware design and test of a gear‑shifting control system of a multi‑gear transmission for electric vehicles［J］. Automotive Innovation， 2019， 2：212-222.
10	SHIMOJO K， YASUI Y， SHIMABUKURO E， et al. New concept sliding mode control for AMT［C］. SAE Paper 2005-01-1594.
11	KIM Sooyoung， OH Jiwon， CHOI Seibum. Gear shift control of a dual-clutch transmission using optimal control allocation ［J］. Mechanism and Machine Theory， 2017， 113：109-125.
12	MENG F， TAO G， CHEN H. Smooth shift control of an automatic transmission for heavy-duty vehicles ［J］. Neurocomputing， 2015， 159： 197-206.
13	SEBASTIAN D， SMYTH R R. Method for controlling AMT system including wheel lock-up detection and tolerance［J］. International Journal of Heave Vehicle System， 2016， 4（6）： 25-34.
14	候延超. 机械式自动变速器选换挡执行机构位置精确控制研究［D］. 秦皇岛：燕山大学， 2018.
	HOU Y C. Research on position accurate control of gearshift actuator for mechanical automatic transmission ［D］. Qinhuangdao： Yanshan University， 2018.
15	任玉平，葛安林. 全电式AMT选换挡系统模糊控制方法研究［J］. 汽车技术， 2004 （8）： 11-14.
	REN Y P， GE A L. Fuzzy control method for the electronic control led and electric gear selecting and shifting system of AMT ［J］. Automobile Technology， 2004，（8）： 11-14.
16	申业，吴光强，罗先银，等. AMT换挡电机的精确跟踪控制［J］. 汽车技术， 2017， 4（6）： 1-4.
	SHEN Y， WU G Q， LUO X Y， et al. Precise tracking control of AMT electric shift actuator ［J］. Automobile Technology， 2017， 4（6）： 1-4.
17	隋立起，王立军，田丰，等. 机械式自动变速器换挡拨叉运动状态估计［J］. 吉林大学学报（工学版）， 2020， 50（4）： 1209-1216.
	SUI L Q， WANG L J， TIAN F， et al. Shift fork motion estimation in mechanical automatic transmission ［J］. Journal of Jilin University （Engineering and Technology Edition）， 2020， 50（4）： 1209-1216.
18	朱会柱，汪秀，袁斌. 基于MOS开关的高频高压脉冲源中电磁兼容问题研究［J］. 电子技术， 2011， 38（3）： 34-36.
	ZHU H Z， WANG X， YUAN B. Investigation on the EMC in HF-HV pulse generator based on MOS switch ［J］. Electronic Technology， 2011， 38（3）： 34-36.
19	蒋元广，李浩楠，彭剑坤，等. 纯电动客车AMT多参数融合换挡规律研究［J］. 机械传动， 2019， 43（7）： 21-26.
	JIANG Y G， LI H N， PENG J K， et al. Research of the AMT multi parameter fusion shift rule of pure electric bus ［J］. Journal of Mechanical Transmission， 2019， 43（7）： 21-26.
20	夏光，涂波涛，唐希雯，等. 基于质量与坡度辨识的汽车自动变速器换挡控制研究［J］. 汽车工程， 2018， 40（3）： 305-312，341.
	XIA G， XU B T， TANG X W， et al. A research on shift control of vehicle automatic transmission based on vehicle mass and road slope identification ［J］. Automotive Engineering， 2018， 40（3）： 305-312，341.
21	史俊武，鲁统利，李小伟，等. 自动变速车辆坡道行驶自适应换挡策略［J］. 农业机械学报， 2011， 42（4）： 1-7.
	SHI J W， LU T L， LI X W， et al. Self-adaptive slope gearshift strategy for automatic transmission vehicles. ［J］. Transactions of the Chinese Society for Agricultural Machinery， 2011， 42（4）： 1-7.
22	雷雨龙，付尧，刘科. 基于扩展卡尔曼滤波的车辆质量与道路坡度估计［J］. 农业机械学报， 2014， 45（I 1）： 9-14．
	LEI Y L， FU Y， LIU K. Vehicle mass and road grade estimation based on extended Kalman filter ［J］. Transactions of the Chinese Society for Agricultural Machinery， 2014， 45（I 1）： 9-14.
23	LINGMAN P， SCHMIDTBAUER B. Road slope and vehicle mass estimation using Kalman filtering［J］. Vehicle System Dynamics， 2002， 37： 12-23.
24	CHENG C， CEBON D. Parameter and state estimation for articulated heavy vehicles［J］. Vehicle System Dynamics， 2011， 49（12）： 399–418.
25	宫新乐. 无人驾驶电动车队运动规划与分布式协同控制研究［D］. 北京：北京理工大学， 2020.
	GONG X L. Motion planning and distributed cooperative control for automated electric vehicle platoon ［D］. Beijing： Beijing Institute of Technology， 2020.
26	于全庆. 电动汽车动力电池多状态联合估计及鲁棒性研究［D］. 北京：北京理工大学， 2019.
	YU Q Q. Research on multi-state joint estimation and robustness of lithium-ion battery in electric vehicle ［D］. Beijing： Beijing Institute of Technology， 2019.

[1]	ZHOU Wei, ZHANG Cheng-Ning, LI Jun-Qiu. [J]. , 2016, 38(12): 1407 -1414 .
[2]	ZONG Yi-Qi, GU Zheng-Qi, LUO Ze-Min, JIANG Cai-Mao, ZHANG Qi-Dong, YANG Zhen-Dong. [J]. , 2016, 38(12): 1427 -1433 .
[3]	ZHANG Ying-Chao, ZHAN Da-Peng, ZHAO Jing, ZHANG Zhe, LI Jie. [J]. , 2016, 38(12): 1434 -1439 .
[4]	TANG You-Ming, YAN Ling-Bo, LUO Qian, CAO Li-Bo. [J]. , 2016, 38(12): 1452 -1458 .
[5]	ZHANG Lei, LU Jian-Wei, JIANG Jun-Zhao, YAN Pei-Lei, LI Lei. [J]. , 2016, 38(12): 1477 -1482 .
[6]	ZHAO Liang, ZHANG Qiang, GUO Kong-Hui. [J]. , 2017, 39(1): 86 -91 .
[7]	SHEN Deng-Feng, WANG Chen, YU Hai-Sheng, ZHANG Tong, YI Xian-Ke. [J]. , 2017, 39(1): 15 -22 .
[8]	ZOU Tie-Fang, HU Lin, LI Ping-Fan, YI Liang. [J]. , 2017, 39(1): 41 -46 .
[9]	ZHOU Kai, ZANG Jing-Lun. [J]. , 2017, 39(2): 127 -132 .
[10]	ZUO Wen-Jie, CHEN Ji-Shun, LI Yi-Wen, LIU Nian. [J]. , 2017, 39(2): 145 -149 .

参数	平均换挡电流/A	最大换挡电流/A	平均换挡电压/V	最大换挡电压/V	换挡时间/ms	换挡位移跟踪误差/mm
修正系统参数（状态1）	4.48	13.36	12.12	22.98	620	0.23
未修正系统参数（状态2）	3.14	15.85	11.17	23.08	1070	0.44
结果对比（基于状态2）	42.68%	-15.71%	8.50%	-0.43%	-42.06%	-47.73%

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State Estimation and Parameter Identification of Shifting Actuator of Automatic Transmission of Electric Vehicles

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