A control algorithm for improving vehicle handling was proposed by applying right angle to the steering wheel,based on the nonlinear adaptive optimal control(NAOC).A nonlinear 4-DOF model was initially developed,then ...A control algorithm for improving vehicle handling was proposed by applying right angle to the steering wheel,based on the nonlinear adaptive optimal control(NAOC).A nonlinear 4-DOF model was initially developed,then it was simplified to a 2-DOF model with reasonable assumptions to design observer and optimal controllers.Then a simplified model was developed for steering system.The numerical simulations were carried out using vehicle parameters for standard maneuvers in dry and wet road conditions.Moreover,the hardware in the loop method was implemented to prove the controller ability in realistic conditions.Simulation results obviously show the effectiveness of NAOC on vehicle handling and reveal that the proposed controller can significantly improve vehicle handling during severe maneuvers.展开更多
为了解决混合动力汽车的实时能量管理及优化问题,在保证不过多简化被控对象的基础上得到最优解,该文提出一种基于V2X(vehicle to vehicle,车车通信,以及vehicle to infrastructure,车与交通设施通信)的分层控制方法。设计了一种分层控制...为了解决混合动力汽车的实时能量管理及优化问题,在保证不过多简化被控对象的基础上得到最优解,该文提出一种基于V2X(vehicle to vehicle,车车通信,以及vehicle to infrastructure,车与交通设施通信)的分层控制方法。设计了一种分层控制器,上层控制器基于交通信号灯正时(signal phase and timing,SPAT)得到目标车速的初始值,并采用多岛遗传算法和非线性模型预测得到最优目标车速。下层控制器根据上层控制器的最优目标车速,采用自适应等效燃油消耗最小原理(adaptive equivalent consumption minimization strategy,A-ECMS),得到发动机和电机的最优输出功率。该文对分层控制方法进行了硬件在环仿真,仿真结果表明,该文提出的分层控制方法可以很好地实现混合动力汽车的实时能量管理,有效地避免混合动力汽车红灯停车,实现良好的车速跟随并减少百公里油耗。该研究可为解决混动力汽车实时能量管理及优化提供参考。展开更多
文摘A control algorithm for improving vehicle handling was proposed by applying right angle to the steering wheel,based on the nonlinear adaptive optimal control(NAOC).A nonlinear 4-DOF model was initially developed,then it was simplified to a 2-DOF model with reasonable assumptions to design observer and optimal controllers.Then a simplified model was developed for steering system.The numerical simulations were carried out using vehicle parameters for standard maneuvers in dry and wet road conditions.Moreover,the hardware in the loop method was implemented to prove the controller ability in realistic conditions.Simulation results obviously show the effectiveness of NAOC on vehicle handling and reveal that the proposed controller can significantly improve vehicle handling during severe maneuvers.
文摘为了解决混合动力汽车的实时能量管理及优化问题,在保证不过多简化被控对象的基础上得到最优解,该文提出一种基于V2X(vehicle to vehicle,车车通信,以及vehicle to infrastructure,车与交通设施通信)的分层控制方法。设计了一种分层控制器,上层控制器基于交通信号灯正时(signal phase and timing,SPAT)得到目标车速的初始值,并采用多岛遗传算法和非线性模型预测得到最优目标车速。下层控制器根据上层控制器的最优目标车速,采用自适应等效燃油消耗最小原理(adaptive equivalent consumption minimization strategy,A-ECMS),得到发动机和电机的最优输出功率。该文对分层控制方法进行了硬件在环仿真,仿真结果表明,该文提出的分层控制方法可以很好地实现混合动力汽车的实时能量管理,有效地避免混合动力汽车红灯停车,实现良好的车速跟随并减少百公里油耗。该研究可为解决混动力汽车实时能量管理及优化提供参考。
