分布式电驱动汽车原地转向机理与控制方法研究  

Research on Mechanism and Control of In-situ Steering for Distributed Drive Electric Vehicles

作　　者：吕皓玉 王翔宇 谢斌[1] 李全通 LYU Hao-yu;WANG Xiang-yu;XIE Bin;LI Quan-tong(Beijing Key Laboratory of Optimized Design for Modern Agricultural Equipment,China Agricultural University,Beijing 100083,China;State Key Laboratory of Automotive Safety and Energy,Tsinghua University,Beijing 100084,China)

机构地区：[1]中国农业大学现代农业装备优化设计北京市重点实验室,北京100083 [2]清华大学汽车安全与节能国家重点实验室,北京100084

出　　处：《中国公路学报》2024年第3期231-244,共14页China Journal of Highway and Transport

基　　金：国家重点研究发展计划项目(2022YFD2001202)。

摘　　要：分布式电驱动汽车能够通过原地转向功能提高车辆的机动性。原地转向下车辆的4个车轮均处于滑移状态,极易发生车身偏移甚至失控。为了实现稳定精准的原地转向控制,分析了原地转向的动力学机理,并提出横摆角速度与滑转率协同的控制策略。基于纵向动力学设计路面附着估计算法,完成原地转向前的路面状况判断;采用了分层式控制架构,上层控制器基于车辆状态协调转矩控制策略,下层控制设计横摆角速度决策框架,根据油门开度计算原地转向的名义横摆角速度,基于二次性能指标的单神经元自适应PID控制算法计算四轮驱动转矩,以实现横摆角速度的跟踪控制,并引入模糊逻辑推理得到四轮期望滑转率,通过PID算法计算驱动转矩调节量,配合横摆角速度转矩控制以抑制转向中心的偏移。仿真测试和实车试验表明:在附着系数一定的情况下,稳态原地转向的轮胎视为刚体,侧偏角与地面侧向反作用力基本不变,试验结果符合所推断的原地转向动力学机理;并验证横摆角速度跟踪控制算法在不同附着系数下具有理想的跟踪效果和鲁棒性,响应速度相比于PID提高46%,最大超调量减小24.0%,平均调节时间缩短1.3 s,平均稳态误差均在0.01 (°)·s^(-1);横摆角速度与滑转率协同控制减小横、纵坐标偏移量2.94、1.69 m,对转向中心偏移起到了抑制作用。Distributed electric drive vehicles can improve vehicle mobility through in-situ steering capabilities.All four wheels of the vehicle are experiencing slipping,creating a situation where the vehicle body is prone to drifting or even losing control.To achieve stable and accurate in-situ steering control,this article analyzed the dynamic mechanism of in-situ steering and proposed a control strategy that coordinates yaw and slip rates.This study designed a road adhesion estimation algorithm based on longitudinal dynamics to complete the evaluation of road conditions before in-situ steering.It adopted a hierarchical control architecture.The upper-layer controller coordinated the torque control strategy based on the vehicle state,and the lower-layer control designed a yaw rate decision-making framework.The nominal yaw rate of the original steering was determined by considering the throttle opening,and the four-wheel-drive torque was calculated using a single-neuron adaptive PID(SNAPID)control algorithm.This algorithm,based on a quadratic performance index,was employed to achieve tracking control of the yaw speed.The expected slip rate of the four wheels was obtained by introducing fuzzy logic reasoning,and the drive torque adjustment was calculated using the PID algorithm and was combined with the yaw rate torque control to suppress the deviation of the steering center.Simulation tests and real vehicle tests show that:when the adhesion coefficient is constant,the tire turning in a steady state is regarded as a rigid body,and the side slip angle and the lateral reaction force on the ground are unchanged,the test results are consistent with the inferred steering dynamics.The test results confirmed that the yaw rate tracking control algorithm exhibits excellent tracking performance and robustness across various attachments.In comparison to PID,the algorithm demonstrated a 46%increase in response speed,a 24.0%reduction in maximum overshoot,and a shortened average adjustment time by 1.3seconds.The average steady-state erro

关 键 词：汽车工程 原地转向 协同控制 分布式驱动汽车 单神经元自适应PID 

分 类 号：U467[机械工程—车辆工程]