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作 者:陈舒平 赵治国[1] 赵坤 CHEN Shuping;ZHAO Zhiguo;ZHAO Kun(School of Automotive Studies,Tongji University,Shanghai 201804,China)
机构地区:[1]同济大学汽车学院,上海201804
出 处:《同济大学学报(自然科学版)》2024年第S01期185-196,共12页Journal of Tongji University:Natural Science
基 金:国家自然科学基金(52172390)。
摘 要:针对紧急避障轨迹跟踪和车辆稳定性多目标控制问题,以四轮独立驱动智能电动汽车为研究对象,提出一种分层结构的轨迹跟踪及稳定性控制方法,上层控制器采用线性时变模型预测控制(LTV MPC)生成期望前轮转角和附加横摆力矩,并通过PID速度跟踪将车速变化考虑到模型预测优化求解中生成总需求转矩,下层控制器采用二次规划将上层计算的广义力最优分配给四个车轮。其中,预测模型为8自由度车辆模型,被控对象为14自由度车辆模型,并建立联合工况刷子轮胎模型。不同车速,路面附着条件以及有无稳定性控制的双移线工况仿真结果表明,所提控制方法具有较好的鲁棒性和轨迹跟踪性能,极限工况下在保证车辆稳定性的同时提高了轨迹跟踪精度。To investigate the multi-objective control problem of trajectory tracking and vehicle stability,a hierarchical coordinated control strategy of trajectory tracking and yaw stability was proposed for four-wheel-independent-drive autonomous electric vehicles.In the upper controller,the linear-time-varying model predictive control(LTV MPC)was employed to generate the desired front road wheel steering angle and yaw moment,and the PID speed control embedded in the model predictive optimization solutions was introduced to generate the desired total driving/braking torque.In the lower controller,the generalized forces from the upper layer were allocated to the four wheels based on quadratic programming.An 8-degree-of-freedom(DOF)vehicle model was used as the prediction model and a high-fidelity 14-DOF vehicle model with longitudinal and lateral combined brush tire model was used as the plant.Numerical simulation results under different speeds,road adhesion coefficients and conditions of whether to consider yaw stability control,demonstrate that the proposed controller possesses good trajectory tracking performance and robustness,which improves the tracking accuracy while ensuring the yaw stability under the limit condition.
关 键 词:四轮独立驱动电动汽车 轨迹跟踪 横摆稳定性 模型预测控制 控制分配
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