Multi-objective Optimization of Differential Steering System of Electric Vehicle with Motorized Wheels

A differential steering system is presented for electric vehicle with motorized wheels and a dynamic model of three-freedom car is built.Based on these models,the quantitative expressions of the road feel,sensitivity,and operation stability of the steering are derived.Then,according to the features of multi-constrained optimization of multi-objective function,a multi-island genetic algorithm(MIGA)is designed.Taking the road feel and the sensitivity of the steering as optimization objectives and the operation stability of the steering as a constraint,the system parameters are optimized.The simulation results show that the system optimized with MIGA can improve the steering road feel,and guarantee the operation stability and steering sensibility.

Primary studies on integration optimization of differential steering of electric vehicle with motorized wheels based on quality engineering

The model of the differential steering system(DSS) of electric vehicle with motorized wheels and the three-degree-of-freedom dynamic model of vehicle are built.Based on these models,the concepts and quantitative expressions of steering road feel,steering portability and steering stability are proposed.Through integrating the Monte Carlo descriptive sampling,elitist non-dominated sorting genetic algorithm(NSGA-II) and Taguchi robust design method,the system parameters are optimized with steering road feel and steering portability as optimization targets,and steering stability and steering portability as constraints.The simulation results show that the system optimized based on quality engineering can improve the steering road feel,guarantee steering stability and steering portability and thus provide a theoretical basis for the design and optimization of the electric vehicle with motorized wheels system.

Multidiscipline collaborative optimization of differential steering system of electric vehicle with motorized wheels

Based on the multidiscipline design optimization theory, a multidiscipline collaborative optimization model of the differential steering system of electric vehicle with motorized wheels is built, with the steering economy as the main system and the steering road feel, the steering flexibility and the mechanic character of the steering sensors as the subsystems. Considering the coupled relationship of each discipline, the main system is optimized by the multi-island algorithm and the subsystems are optimized by the sequential quadratic programming algorithm. The simulation results show that the steering economy can be optimized by the collaborative optimization, and that the system can get good steering road feel, good steering flexibility and good mechanic character of the steering sensors.

Integrated energy-oriented lateral stability control of a four-wheelindependent-drive electric vehicle

Improving the energy efficiency of an electric vehicle(EV) is an effective approach to extend its driving range. This paper proposes an integrated energy-oriented lateral stability controller(IESC) for a four-wheel independent-drive EV(4 WID-EV) to optimize its energy consumption while maintaining vehicular stability during cornering. The IESC is a hierarchical controller with two levels. The high-level decision-making controller determines the virtual control inputs, i.e., the desired additional yaw moment and total wheel torque, while the low-level controller allocates the motor torques according to the virtual control inputs.In the high-level controller, the desired additional yaw moment is first calculated using a linear quadratic regulator(LQR) to minimize the control expenditure. Meanwhile, a stability weighting factor(SWF) based on phase plane analysis is proposed to adjust the additional yaw moment, which can reduce the additional energy consumption caused by the mismatch between the reference model and the actual vehicle. In addition to the yaw moment, the desired total wheel torque is calculated using a proportional-integral(PI) controller to track the desired longitudinal velocity. In the low-level controller, a multi-objective convex-optimization problem is established to optimize the motor torque by minimizing the energy consumption and considering the tire-road frictional limit and motor saturation. A globally optimal solution is obtained by using an active-set method. Finally,double-lane change(DLC) simulations are conducted using Car Sim and MATLAB/Simulink. The simulation results demonstrate that the proposed controller achieves great lateral stability control performance and reduces the energy consumption by5.23% and 2.95% compared with the rule-based control strategy for high-and low-friction DLC maneuvers, respectively.

Lateral stability region conservativeness estimation and torque distribution for FWIA electric vehicle steering

Estimation of the lateral stability region and torque distribution on steering is very important to improve stability in lateral handling for all wheel drive electric vehicles.Based on the built-nonlinear vehicle dynamic model,the lateral stability region of the vehicle related to steering is estimated using Lyapunov function.We obtained stable equilibrium points of non-straight driving according to the estimated lateral stability region and also reconstructed the Lyapunov function matrix,which proved that the closed-loop system composed of yaw rate and lateral velocity is satisfied with negative definite property.In addition,the designed controller dynamically allocates the drive torque in terms of the vertical load and slip rate of the four wheels.The simulation results show that the estimated lateral stability region and the designed controller are satisfactory in handling stability performance against different roads and vehicle parameters.

两轴径向独立轮副轨道车辆动力学性能

针对独立车轮导向问题提出后倾角导向方法,使独立轮副轨道车辆获得自导向能力。阐述车辆的自导向原理,利用横向轮轨力和后倾角力臂形成摇头力矩,使独立车轮自动转向。关于中心对称的前后独立轮副分别向相反方向转向,使独立车轮处于径向位置。采用多体动力学方法分析独立轮副轨道车辆的自导向性能。结果表明:在直线轨道上,后倾角对车辆横向位移和摇头角的影响明显。带后倾角车辆出现类蛇行运动现象。具有后倾角的车辆在直线轨道上能够自动复位。在曲线轨道上,左前导向轮具有较大的冲角。后倾角能够使车辆动态对中,最终回到轨道中心线位置。带后倾角的独立轮副轨道车辆在曲线轨道上具有有限的导向能力。

四轮转向干预下电动助力转向控制策略研究

四轮转向(4WS)车辆相较于前轮转向(FWS)车辆具有更高的灵活性,其后轮转向在提高车辆操稳性的同时转向阻力矩也发生变化,使得原电动助力转向系统助力策略与四轮转向车辆不匹配,对行车安全产生影响.本文以线性二自由度车辆模型为基础,对比分析了前轮转向车辆与四轮转向车辆的转向特性,提出电动助力转向修正控制策略.仿真结果表明,角阶跃工况下,有助力修正的四轮转向车辆,驾驶员操纵方向盘力矩与驾驶前轮转向车辆基本一致,既保证了四轮转向车辆低速时的操纵轻便性,也兼顾了高速时的操纵稳定性.

分布式驱动电动汽车执行器失效容错控制研究

为了提高单电机故障状态下分布式驱动电动汽车的稳定性,提出了一种驱动力重构和主动前轮转向(AFS)结合的容错控制方法。首先,设计滑模控制器,控制输入量为横摆角速度和质心侧偏角,进而对所需横摆力矩和前轮附加转角进行控制。其次,建立电机故障状态下的整车驱动力优化分配模型。当车辆电机出现故障时,运用二次规划算法对各电机转矩进行重构分配。同时,当某一电机发生故障且同侧电机出现输出饱和而无法提供足够的横摆力矩时,通过主动前轮转向提供附加横摆力矩。最终搭建CarSim/Simulink联合仿真模型进行验证,结果显示,所采用的容错控制方法可有效提高车辆稳定性和动力性。

小曲率路面车辆差动转向与横摆稳定性集成控制研究

为减小车辆在前轮转向系统失效的负面影响,保证转向系统的瞬态控制性能,本文提出差动转向控制与横向稳定性控制相结合的控制方法,通过调节左右轮毂电机转矩形成横摆力矩,实现对系统完全失效车辆的转向控制与横向稳定性控制。首先设计基于LQR差动转向控制器跟踪参考前轮转角与参考横摆角速度,保证车辆轨迹跟踪能力,然后设计基于模糊PID横向稳定性控制器跟踪参考质心侧偏角,保证车辆横摆稳定性,两者构成双闭环控制系统将控制量最终转化为横摆力矩,实现车辆的集成控制。最后通过Simulink-Carsim联合仿真验证,仿真结果表明差动转向系统能够在前轮转向系统失效情况下实现车辆转向控制,并在横向稳定性控制系统的作用下有效地提高了车辆瞬态控制性能。

融合模式决策的4WIS车辆路径规划方法

针对四轮独立转向(four-wheel independent steering,4WIS)车辆的路径规划问题,提出了一种融合模式决策的图搜索算法.首先,对4WIS车辆三种运动模式进行建模,并分析其运动模式的运动特性,据此设计多模式节点拓展策略,实现了4WIS车辆多运动模式与路径规划的融合.然后,针对最优节点选取和运动模式决策问题,设计了多目标代价函数,引导4WIS车辆合理切换运动模式,并生成平滑路径.最后,在MATLAB软件上进行仿真实验,在多种场景中测试所提出算法,验证其可行性与有效性.结果表明:提出的算法在路径规划中考虑了三种运动模式的优化组合与模式切换问题,能实现最优运动模式序列和最短路径规划.且该算法求解效率高,所规划路径优异,能充分发挥4WIS车辆的高灵活性与高通过性,有效解决其路径规划问题.

基于多胞体系统的FWID EV鲁棒加权增益调度轨迹跟踪控制

为了提高四轮独立驱动电动汽车(FWID EV)轨迹跟踪控制性能,针对车辆横向运动系统的不确定性与非线性问题,考虑转向执行机构的动态特性,提出了基于线性变参数(LPV)的鲁棒加权增益调度轨迹跟踪控制策略。首先利用凸分解技术将LPV系统转化为有限多胞顶点凸组合的多胞体系统,然后基于离线设计的每个多胞顶点控制器和线性组合在线计算任意时变参数对应的系统控制器参数,并利用MATLAB和CarSim进行联合仿真。结果表明:在加速变道场景下,所设计的控制器可以保证横向偏移误差不超过2 cm,横向偏移平均绝对误差不超过0.9 cm的较高跟踪精度及行驶稳定性和鲁棒性。

四轮独立驱动汽车偏转 差动协同转向路径跟踪

为改善四轮独立驱动汽车在不同车速与路面附着系数下的路径跟踪效果,提出了偏转差动协同转向控制策略。在二自由度动力学模型的基础上,建立多点预瞄与线性二次调节(LQR)结合的前轮偏转转向路径跟踪、滑模控制与四轮转矩优化分配结合的四轮差动转向路径跟踪,采用模糊控制对偏转转向与差动转向路径跟踪的权重进行自适应分配,建立包含路径跟踪层与转角、转矩分配控制层的偏转差动协同控制策略。利用Carsim与Simulink分别建立协同转向路径跟踪与LQR偏转转向路径跟踪联合仿真平台,取车速为54、72 km/h与路面附着系数为0.3、0.8的双移线工况进行仿真得出结论:相较于LQR偏转转向路径跟踪,协同转向路径跟踪在各工况下的横向跟踪精度与稳定性均有所提高。

低附着路面条件下四轮独立驱动转向电动车稳定性控制研究

针对四轮独立驱动转向车辆在低附着路面的稳定性问题,提出了一种协调稳定性控制器。首先,基于模糊理论设计了主动后轮转向(active rear wheel steering,ARS)控制器,实现减小质心侧偏角的效果;然后,基于等效滑模变结构设计了直接横摆力矩控制(direct yaw moment control,DYC)控制器,以控制横摆角速度为目标;最后,基于Carsim/Simulink仿真平台搭建稳定性算法模型,进行了低附着系数双移线工况仿真对比。结果表明,所提出ARS和DYC协调控制算法能有效改善车辆在低附着路面上的行驶稳定性。

基于模糊滑模直接横摆力矩的车辆横摆稳定性控制

为了避免车辆发生横向失稳的风险,根据四轮独立驱动电动汽车四轮驱动/制动力矩独立可控的特点,提出了一种具有上层控制器和下层控制器两层结构的模糊滑模直接横摆力矩控制策略。上层控制器采用模糊滑模控制器计算车辆总的需求横摆力矩,并对4个车轮纵向力进行分配。下层控制器将轮胎纵向力转化为对轮胎滑动率的控制,并通过控制4个车轮的力矩使轮胎纵向力得到实现。仿真结果表明,该模糊滑模直接横摆力矩控制策略在不同的附着路面条件下都能保证车辆的横向稳定性,并能削弱传统滑模控制器造成的系统抖振。

分布式驱动电动汽车四轮转向与横摆力矩集成控制研究

针对四轮独立驱动与独立转向的分布式驱动电动汽车稳定性控制问题,提出了一种四轮转向与横摆力矩集成控制策略。采用分层控制结构,基于模糊理论设计上层控制器,根据期望横摆角速度、期望质心侧偏角与实际值的偏差,计算附加后轮转角和附加横摆力矩;下层控制器包括四轮转角控制器和四轮力矩分配器,附加后轮转角控制器根据转向盘转角和车速分别采用比例前馈加模糊反馈或阿克曼转向进行附加后轮转角控制,四轮力矩分配器根据附加横摆力矩需求采用二次规划算法对四轮力矩进行优化分配。选取典型实验工况,通过联合仿真实验对后轮转向与横摆力矩集成控制策略进行验证。结果表明:集成控制策略能有效提高分布式驱动电动汽车稳定性。

轮毂电机驱动越野车原地转向控制

针对基于阿克曼转向的越野车最小转弯半径大、转向机动性不足的问题,利用轮毂电机驱动车辆转矩独立可控的优势,开发了路面自适应的原地转向控制策略。构建整车七自由度原地转向动力学模型,阐释原地转向过程中纵横向耦合运动轮胎力的演变规律,建立原地转向阻力矩和横摆力矩随车轮滑转率、路面附着系数变化的量化模型。以转向动力响应性为优化目标设计了不同附着条件下的横摆角速度期望轨迹,并以各轮滑转率安全阈值作为稳定性约束以减小转向中心偏移量,执行层基于模型预测算法进行横摆角速度的跟踪控制,同时引入自适应滑模控制器反馈调节车轮滑转率以确保纵横向运动的稳定性。仿真测试与实车试验表明,开发的原地转向控制策略在高、中、低附路面下均实现了期望原地转向轨迹的精确跟踪,并将转向中心偏移量限制在500 mm以内,提高了越野车原地转向灵活性和横向稳定性,实现了“既快又稳”的原地转向。

独立驱动电动汽车质心侧偏角融合估计方法

针对传统质心侧偏角估计精度低、实时性差等问题,把四轮独立驱动电动汽车作为研究对象,提出一种基于强跟踪卡尔曼滤波及无迹卡尔曼滤波融合估计的质心侧偏角估计方法。由于汽车在侧向加速度较小时车辆动力学特性基本呈线性变化,此时通过强跟踪卡尔曼滤波快速估计,当汽车侧向加速度较大时车辆动力学特性趋于非线性变化,通过无迹卡尔曼滤波准确估计。最后将两种估计方法的数据融合,完成不同车速不同工况下对车辆质心侧偏角的估计。搭建Simulink-Carsim联合仿真平台对提出的方法进行验证,结果表明该方法在保证估计精度的同时具有较好的实时跟踪效果及鲁棒性。

四轮独立驱动EV侧向稳定性H∞鲁棒容错控制

为解决参数不确定性四轮独立驱动电动汽车发生执行器及传感器故障时车辆侧向稳定性控制问题,提出一种H∞鲁棒容错控制方法。运用故障矩阵函数引入车辆连续性故障,建立了考虑执行器及传感器故障的二自由度车辆参数不确定性动力学模型。运用线性矩阵不等式求解方法设计车辆侧向稳定性H∞鲁棒容错控制器,保证车辆动力学系统渐近稳定性及抗干扰能力,实现控制系统H∞鲁棒性能满足给定的干扰衰减指标。搭建CarSim与MATLAB/Simulink联合仿真实验平台,验证控制器的有效性。仿真实验表明,所设计H∞鲁棒容错控制器能有效提升了车辆的侧向稳定性及安全性,对车辆故障具有良好的容错控制能力。

分布式驱动电动汽车的横向稳定性控制研究

为提高分布式驱动电动汽车的横向稳定性,旨在通过协同控制车辆的主动前轮转向系统与直接横摆力矩控制系统来实现。首先,基于整车线性二自由度模型,根据质心侧偏角-质心侧偏角速度的相平面描述的稳定区域边界设计上层控制器,再由相平面策略确定下层控制器中的主动前轮转向控制器和直接横摆力矩控制器的协调控制系数;然后,通过变结构滑模控制的下层控制器计算所需的附加前轮转角和附加横摆力矩来调整车辆驱动力矩分配;最后,分别进行双移线工况和阶跃工况下的硬件在环试验分析,试验结果表明,协同控制分布式驱动电动汽车的主动前轮转向系统与直接横摆力矩控制系统能更好地提高其横向稳定性。

四轮驱动电动汽车转向行驶自适应预测控制

为改善四轮驱动电动汽车在转向行驶工况下因车速较快导致的横向稳定性下降问题,提出了一种基于模型预测控制(Model Predictive Control,MPC)的自适应预测控制方法。在建立车辆三自由度模型、轮胎模型和驾驶员模型的基础上,通过结合模型预测控制和比例积分微分(Proportional Integral Derivative,PID)控制,设计了自适应预测控制器,以实现四轮驱动电动汽车横向稳定控制。通过CarSim软件与Simulink软件进行联合仿真,结果表明,与传统PID控制相比,自适应预测控制的侧向位移减小了7.9%,横摆角速度降低了37.5%,所提出的控制方法有效提高了期望路径的跟踪精度,改善了四轮驱动电动汽车在转向行驶过程中的横向稳定性。