基于直接横摆力矩控制的FSAE纯电动赛车操纵稳定性控制策略
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摘要
针对双电机驱动FSAE纯电动赛车操纵稳定性控制问题,提出了基于直接横摆力矩控制的操纵稳定性控制策略。采用扩展卡尔曼滤波对实际质心侧偏角进行估计,分别设计了基于PID控制、基于模糊逻辑控制以及基于PID模糊逻辑联合控制的附加横摆力矩控制器;并在方向盘转角阶跃工况以及双移线工况下,基于Matlab/Simulink平台进行了仿真对比。利用A&D5435半实物仿真平台和Matlab/Simulink代码自动生成技术,搭建了FSAE纯电动赛车硬件在环试验平台,并进行了双移线工况的实车试验验证。结果表明:文中提出的PID模糊逻辑联合控制策略相比于无控制和PID控制横摆角速度的稳态值和极值最多分别减小12. 17%和43. 87%,质心侧偏角的稳态和值极值最多分别减小8. 4%和68. 53%,并且收敛速度变快,提高了车辆的操纵稳定性。
Aiming at the stability control problem of distributed drive FSAE pure electric vehicles,direct yaw moment control strategy of handing stability is studied. Based on the extended Kalman filter method,the side slip angle is estimated. The PID controller,the fuzzy logic controller,the PID and fuzzy logic joint controller of the additional yaw moment are designed respectively; and under the steering wheel step input angle operating condition and the double-shift line operating condition,based on the MATLAB/Simulink platform,the designed control strategies of handling stability are simulated and compared. Using A&D 5435 hardware-in-theloop simulation platform and Matlab/Simulink simulation code auto-generation technology,the hardware-in-the-loop test platform of FSAE pure electric racing car was built,and the real vehicle test verification of double-shift line conditions was carried out. The results show that compared with no control and PID control alone,the proposed PID and fuzzy logic joint control strategy can significantly reduce the steady state value and the extreme value of the side slip angle by 12. 17% and 43. 87% at most respectively and those of the yaw rate by8. 4% and 68. 53% at most respectively,and the convergence rates of the two both become faster,so the handling stability of the vehicle is improved.
Aiming at the stability control problem of distributed drive FSAE pure electric vehicles,direct yaw moment control strategy of handing stability is studied. Based on the extended Kalman filter method,the side slip angle is estimated. The PID controller,the fuzzy logic controller,the PID and fuzzy logic joint controller of the additional yaw moment are designed respectively; and under the steering wheel step input angle operating condition and the double-shift line operating condition,based on the MATLAB/Simulink platform,the designed control strategies of handling stability are simulated and compared. Using A&D 5435 hardware-in-theloop simulation platform and Matlab/Simulink simulation code auto-generation technology,the hardware-in-the-loop test platform of FSAE pure electric racing car was built,and the real vehicle test verification of double-shift line conditions was carried out. The results show that compared with no control and PID control alone,the proposed PID and fuzzy logic joint control strategy can significantly reduce the steady state value and the extreme value of the side slip angle by 12. 17% and 43. 87% at most respectively and those of the yaw rate by8. 4% and 68. 53% at most respectively,and the convergence rates of the two both become faster,so the handling stability of the vehicle is improved.
引文
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[18]郭孔辉,付皓,丁海涛.基于扩展卡尔曼滤波的汽车质心侧偏角估计[J].汽车技术,2009(4):1-3+44.
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[25] YI K,CHUNG T,KIM J,et al. An investigation into differential braking strategies for vehicle stability control[J]. Journal of Automobile Engineering,2003,217(12):1081-1094.
[26]黄程程.基于自适应卡尔曼滤波的汽车质心侧偏角估算研究[D].长春:吉林大学,2011.
[2]褚端峰.客车行驶稳定性控制的关键技术研究[D].武汉:武汉理工大学,2010.
[3]余志生.汽车理论[M]5版.北京:机械工业出版社,2012.
[4] REEDY J,LUNZMAN S,MEKARI B. Model based design accelerates the development of mechanical locomotive controls[J]. Intelligent Vehicles Symposium IEEE,2010,32(14):1098-1103.
[5] NAGAI M,SHINO M,GAO F. Study on integrated control of active front steer angle and direct yaw moment[J]. Jsae Review,2002,23(3):309-315.
[6] LU J,MESSIH D,SALIB A,et al. An enhancement to an electronic stability control system to include a rollover control function[J]. Sae Transactions,2007,116:303-313.
[7] SILL J H,AYALEW B. Saturation balancing control for enhancing dynamic stability of vehicles with independent wheel drives[C]∥SAE 2011 World Congress Exhibition. SAE,2011.
[8]王金湘,陈南,皮大伟.基于横摆角速度变门限值的车辆稳定性控制策略及实车场地试验[J].汽车工程,2008,30(3):222-226.
[9]陈无畏,祝辉.基于状态识别的整车操纵性和平顺性的协调控制[J].机械工程学报,2011,47(6):121-129.
[10] TAHAMI F,FARHANGI S,KAZEMI R. A fuzzy logic direct yaw-moment control system for all-wheeldrive electric vehicles[J]. Vehicle System Dynamics,2004,41(3):203-221.
[11]王其东,黄鹤,陈无畏,等.基于自适应FFRLS的汽车前后轴侧偏刚度估计[J].机械工程学报,2012,48(12):110-117.
[12]玄圣夷,宋传学,靳立强,等.基于多级鲁棒PID控制的汽车稳定性控制策略[J].吉林大学学报(工学版),2010,40(1):13-18.
[13]张金柱,张洪田,孙远涛.电动汽车稳定性的横摆力矩控制[J].电机与控制学报,2012,16(6):75-80.
[14]肖闯.汽车稳定性控制方法仿真研究[D].长沙:湖南大学,2007.
[15]吕红明,陈南,王琪. Matlab环境下车辆的开环操纵稳定性仿真[J].盐城工学院学报(自然科学版),2004,17(1):21-24.
[16] ZANTEN A T V. VDC,the vehicle dynamics control system of Bosch[J]. Advancements in Abs/tcs&Brake Technology Sae,1995.
[17]刘旭程.基于差动制动的汽车横向稳定性控制研究及仿真分析[D].南宁:广西大学,2015.
[18]郭孔辉,付皓,丁海涛.基于扩展卡尔曼滤波的汽车质心侧偏角估计[J].汽车技术,2009(4):1-3+44.
[19] SASAKI H,NISHIMAKI T. A side slip angle estimation using neural network for a wheeled vehicle[J].SAE Technical Paper,2000.
[20]郭张军,徐建光,刘佳佳.基于Kalman滤波融合算法的某坝基水平位移综合信息提取[J].盐城工学院学报(自然科学版),2010,23(2):30-34.
[21] BAKKER E. A new tire model with an application in vehicle dynamics studies[J]. SAE Technical Paper,1989:98.
[22]周红妮.车辆稳定性控制方法于策略的比较研究[D].武汉:武汉科技大学,2006.
[23]刘曙光,魏俊民,竺志超.模糊控制技术阅[M].北京:中国纺织出版社,2002.
[24]郭应时,袁伟.汽车试验学[M].北京:人民交通出版社,2006.
[25] YI K,CHUNG T,KIM J,et al. An investigation into differential braking strategies for vehicle stability control[J]. Journal of Automobile Engineering,2003,217(12):1081-1094.
[26]黄程程.基于自适应卡尔曼滤波的汽车质心侧偏角估算研究[D].长春:吉林大学,2011.