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基于CKF的四轮驱动电动汽车质心侧偏角估计

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针对传统质心侧偏角观测精度不高、实时性能差的问题,提出了一种基于CKF算法的质心侧偏角观测器.首先基于CKF算法结合Dugoff轮胎模型,实时观测路面附着系数,计算实时的轮胎力.再结合七自由度整车模型,基于CKF算法,实时、精确观测车辆的质心侧偏角.最后,利用Simulink/Carsim联合仿真验证平台和硬件在环平台进行仿真验证.试验结果表明,CKF算法相比与传统无迹卡尔曼滤波估计精度更高、实时性能更好,较好的改善了传统质心侧偏角观测器在非线性条件下的观测精度.
Estimation of Sideslip Angle of Four Wheel Drive Electric Vehicle Based on Dual CKF
Aiming at the problems of low accuracy and poor real-time performance of traditional sideslip angle observation,a sideslip angle observer based on a CKF algorithm is proposed.Firstly,based on the CKF algorithm and Dugoff tire model,the road adhesion coefficient is observed in real-time to calculate the real-time tire force.Combined with the seven degrees of freedom vehicle model and based on the CKF algorithm,the sideslip angle of the vehicle can be observed in real-time and accurately.Fi-nally,the Simulink/CarSim joint simulation verification platform and hardware in the loop platform are used for simulation veri-fication.The experimental results show that compared with the traditional unscented Kalman filter,the estimation algorithm based on dual volume Kalman Filter has higher estimation accuracy and better real-time performance,and better improves the observation accuracy of the traditional sideslip angle observer under nonlinear conditions.

Cubature Kalman FilterAdhesion Coefficient of PavementSideslip AngleFour Wheel Drive Elec-tric Vehicle

苏忆、徐律、李捷辉

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无锡商业职业技术学院,江苏 无锡 214153

江苏大学,江苏 镇江 212013

容积卡尔曼滤波 路面附着系数 质心侧偏角 四轮驱动电动汽车

江苏省第六期"333高层次人才培养工程"第三层次培养对象江苏省高等学校基础科学(自然科学)研究面上项目无锡商业职业技术学院校级课题

20223-16-81622KJD460008KJZX21603

2024

机械设计与制造
辽宁省机械研究院

机械设计与制造

CSTPCD北大核心
影响因子：0.511
ISSN：1001-3997
年,卷(期)：2024.402(8)