摘要
为提高分布式驱动电动汽车在极限工况下的横向稳定性,针对车辆模型参数不确定性,提出了一种基于主动前轮转向(AFS)和直接横摆力矩控制(DYC)的底盘集成控制系统。该系统采用模块化架构。首先,设计基于扰动观测和滑模控制的AFS控制器;其次,构建基于线性矩阵不等式的AFS&DYC集成控制器,利用径向基神经网络自适应逼近不确定项;进而根据当前车辆状态计算稳定因子和权重系数,以实现不同车辆状态下两组控制器的协调;最后通过二次规划实现转矩优化分配。联合仿真结果表明,所提出的集成控制系统有效提升了车辆在极限工况下的横向稳定性。
To enhance the lateral stability of distributed drive electric vehicles under extreme conditions such as high speed or low adhesion,this paper addresses the issue of parameter uncertainties in the vehicle dynamics model by proposing an integrated chassis control system based on the coordination of Active Front Steering(AFS)and Direct Yaw Moment Control(DYC).The designed stability control system adopts a modular architecture consisting of four modules.First,an AFS controller based on a nonlinear disturbance observer and integral terminal sliding mode control is designed.Second,considering model parameter uncertainties,an integrated AFS&DYC controller based on Linear Matrix Inequalities(LMI)is developed,which employs a Radial Basis Function(RBF)neural network to adaptively approximate the uncertain terms in the control law.Furthermore,stability factors and weighting coefficients are calculated based on real-time vehicle states to achieve the desired additional steering angle and yaw moment,enabling switching and coordination between the two controllers under different vehicle conditions.Finally,a torque distribution controller based on quadratic programming is designed to optimize the drive torque of the four wheels.The proposed algorithms are validated through co-simulation using MATLAB/Simulink and Carsim.Simulation results demonstrate that the proposed AFS controller ensures vehicle stability,though its effectiveness is limited by tire slip characteristics;meanwhile,the overall integrated control performs effectively,ensuring lateral stability under extreme conditions with strong robustness.
作者
黄继刚
张涌
毛晓露
Huang Jigang;Zhang Yong;Mao Xiaolu(Nanhang Jincheng College,Nanjing 210016;Nanjing Forestry University,Nanjing 210016)
出处
《汽车技术》
北大核心
2025年第11期1-10,共10页
Automobile Technology
基金
江苏省重点研发项目(BE2022053-2)。
