基于双轮式电机再生制动车辆稳定性集成控制研究

以双轮式电机前驱电动汽车制动系统为研究对象,把双电机再生制动、液压制动、稳定性控制集成在一起,开发了再生制动系统协调控制器。根据车辆制动需求、车辆状态、系统储能状态等确定车辆制动模式及分配制动力矩,并根据车辆实时稳定性状况由双轮式电机再生制动提供车辆稳定性控制力矩。仿真和试验结果表明,在车辆转弯制动工况中采用所述集成协调控制器比采用电机单边独立控制稳定性控制效果更好。     

弯道路面车辆制动稳定性控制仿真研究

车辆在弯道路面行驶,由于离心力的作用,制动易导致车辆失去横向稳定性。本文分析了车辆弯道制动时ABS控制方法存在的不足,提出了车辆ABS与横摆力矩控制的协调控制策略。利用模糊控制原理设计了横摆力矩控制器,在车辆ABS的基础上,通过对车辆的横摆力矩控制和车轮滑移率的调节,实现了制动过程中对附加横摆力矩的动态调整,从而提高车辆在弯道路面上的制动稳定性,通过在低附着系数弯道路面上车辆制动力矩分配仿真验证了该控制方法的有效性。     

整车制动性能主观评价方法研究与应用

在车辆开发测试阶段,从客户实际用车角度出发,遵循顾客的车辆驾驶习惯,对整车制动性能进行主观评价,分别对制动人机工程、制动踏板感、制动效能、制动方向稳定性、制动热稳定性、制动振噪6个维度进行主观评价,从车辆开发早期阶段参与同步开发评价,联合客观测试试验,对车辆制动性能开发提出改善方向及意见。     

采用准中性转向参考模型的操纵稳定性控制技术

设计了一种提高车辆操纵稳定性的准中性转向参考模型。该模型在零侧偏角参考模型的基础上增加了中性转向特性以驾驶员一车辆闭环系统的稳定性。分别用这两种参考模型进行车辆制动时运动参数变化的仿真试验,试验表明准中性转向参考模型可以提高车辆制动时的操纵稳定性。     

EBD系统参数对乘用车制动性能的影响分析

旨在分析EBD系统参数对乘用车制动性能的影响,采用实验方法进行研究,实验结果表明,EBD系统参数对乘用车制动性能有显著影响。在制动力分配方面,不同参数的调整导致前后轮的制动力分配比例发生变化,进而影响了车辆的制动性能。在刹车距离方面,某些参数的调整使得车辆在制动时能够更快地停下来,从而缩短了刹车距离。此外,参数的优化还能够提高车辆的稳定性,减少制动时的侧滑和不稳定现象。合理调整和优化EBD系统参数能够显著改善乘用车的制动性能,提高制动力分配的效果,缩短刹车距离,并增加车辆的稳定性。     

基于集成式线控液压制动系统的车辆稳定性控制CSCD

为提高汽车在极限工况下的行驶稳定性,提出了一种基于集成式线控液压制动(IEHB)系统的车辆动力学稳定性控制策略。在多学科领域复杂系统建模仿真平台(AMESim)中建立了IEHB执行机构、15自由度非线性车辆动力学物理仿真模型;采用分层控制构架,运用线性比例控制与非线性补偿控制设计了横摆力矩控制层,设计了制动力矩分配层和执行层以保证被控车辆对参考模型层输出的跟踪品质。结果表明:相比于基于传统车身电子稳定性控制系统(ESC)的动力稳定性控制系统,横摆角速度峰值跟踪误差减少13.6%,收敛时间缩短1.3 s,侧倾角、侧偏角、侧向加速度等也均有明显改善,车辆行驶稳定性显著提高。因而,本控制方法能确保车辆在极限工况下快速、准确地跟踪参考模型输出。     

乘用车制动踏板感觉的综合评价

通过对车辆制动踏板的整车道路试验、分析及踏板感觉的主观评价,提出了对车辆制动踏板感觉综合评价的方法——制动感觉指数。通过该指数全面地分析车辆在制动过程中驾驶员脚下的感受,包括踏板力、踏板行程和制动减速度等,以量化参数的方法来描述制动感觉所涉及的各项指标,给工程设计和用户实际感受之间提供了转换的桥梁。     

基于模型预测的横摆和侧向稳定性控制

针对无人驾驶车辆路径跟踪过程中横摆和侧向稳定性控制,提出一种转向和制动的模型预测控制方案。控制方法基于3自由度车辆模型,控制目标是通过制动和转向的联合来跟踪期望路径。该控制方案依赖于非线性预测控制方法的预测功能,搭建基于MPC(Model Predictive Control,模型预测控制)的车辆主动转向和制动控制系统。通过Car Sim和Simulink联合仿真试验进行验证,证明所提出方法的有效性。     

ABS的综合性能评价体系及道路试验研究

介绍了装备ABS车辆制动综合性能的评价体系,并探讨了道路试验项目及其评价内容。重点阐述了ABS车辆的 附着系数的测定方法和道路试验项目,提出侧向稳定性作为ABS性能评价项目之一的可行性。     

一种降低人-地撞击损伤的车辆制动控制方法

为降低车人碰撞事故中人与地面撞击所致损伤,提出一种车辆制动控制策略.该策略在检测到人体头部与车辆首次接触后松开车辆制动,之后依据若干准则再次完全制动车辆直到车辆停止.选择10种车型、两种制动方法(完全制动和控制制动)和一个虚拟仿真系统(包含3种车速×4种行人尺寸×2种行人步态)设计了共480次MADYMO仿真试验.结果...     

Vehicle Dynamic Control for In-Wheel Electric Vehicles Via Temperature Consideration of Braking Systems

?Vehicle dynamic control (VDC) systems play an important role with regard to vehicle stability and safety when turning. VDC systems prevent vehicles from spinning or slipping when cornering sharply by controlling vehicle yaw moment, which is generated by braking forces. Thus, it is important to control braking forces depending on the driving conditions of the vehicle. The required yaw moment to stabilize a vehicle is calculated through optimal control and a combination of braking forces used to generate the calculated yaw moment. However, braking forces can change due to frictional coefficients being affected by variations in temperature. This can cause vehicles to experience stability problems due an improper yaw moment being applied to the vehicle. In this paper, a brake temperature estimator based on the finite different method (FDM) was proposed with a friction coefficient estimator in order to solve this problem. The developed braking characteristic estimation model was used to develop a VDC cooperative control algorithm using hydraulic braking and the regenerative braking of an in-wheel motor. Performance simulations of the developed cooperative control algorithm were performed through cosimulation with MATLAB/Simulink and CarSim. From the simulation results, it was verified that vehicle stability was ensured despite any changes in the braking characteristics due to brake temperatures.     

A study on heavy duty truck stability control by braking force control

Nowadays we are discussing a vehicle stability control system which freely controls the braking force of each wheel to apply the yaw moment and decelerate the vehicle. The system drastically improves the vehicle cornering performance and stabilizes the vehicle behaviour in its critical area. This paper discusses points to notice in the case of applying this technique for heavy duty trucks, and describes the possibility of the stabilization for vehicle cornering behavior of a heavy duty truck.     

Study on integrated control of active front steer angle and direct yaw moment

This study proposes a control system to improve vehicle handling and stability under severe driving conditions by actively controlling the front steering angle and the distribution of braking forces on four tires. With the application of a model-matching control technique, this proposed control system makes the performance of the actual vehicle model follow that of an ideal vehicle model with consideration of nonlinearity of tire characteristics. Finally, this paper investigates the effectiveness of control system during the following conditions: braked cornering, lane change and side wind disturbance.     

轮胎附着极限下差动制动对汽车横摆力矩的影响

本文以纵滑－侧偏联合工况的稳态轮胎模型为基础，分析了汽车极限转向条件下制动作用于不同车轮时对汽车横摆力矩的影响，并通过整车动力学仿真进行了验证，研究结果为利用差动制动控制提高汽车的高速操纵稳定性提供了动力学依据。     

Cooperative regenerative braking control for front-wheel-drive hybrid electric vehicle based on adaptive regenerative brake torque optimization using under-steer index

In this study, cooperative regenerative braking control of front-wheel-drive hybrid electric vehicle is proposed to recover optimal braking energy while guaranteeing the vehicle lateral stability. In front-wheel-drive hybrid electric vehicle, excessive regenerative braking for recuperation of the maximum braking energy can cause under-steer problem. This is due to the fact that the resultant lateral force on front tire saturates and starts to decrease. Therefore, cost function with constraints is newly defined to determine optimum distribution of brake torques including the regenerative brake torque for improving the braking energy recovery as well as the vehicle lateral stability. This cost function includes trade-off relation of two objectives. The physical meaning of first objective of cost function is to maximize the regenerative brake torque for improving the fuel economy and that of second objective is to increase the mechanical-friction brake torques at rear wheels rather than regenerative brake torque at front wheels for preventing front tire saturation. And weighting factor in cost function is also proposed as a function of under-steer index representing current state of the vehicle lateral motion in order to generalize the constrained optimization problem including both normal and severe cornering situation. For example, as the vehicle approaches its handling limits, adaptation of weighting factor is possible to prioritize front tire saturation over increasing the recuperation of braking energy for driver safety and vehicle lateral stability. Finally, computer simulation of closed loop driver-vehicle system based on Carsim? performed to verify the effectiveness of adaptation method in proposed controller and the vehicle performance of the proposed controller in comparison with the conventional controller for only considering the vehicle lateral stability. Simulation results indicate that the proposed controller improved the performance of braking energy recovery as well as guaranteed the vehicle lateral stability similar to the conventional controller.     

Emergency steering control of autonomous vehicle for collision avoidance and stabilisation

ABSTRACT

Collision avoidance and stabilisation are two of the most crucial concerns when an autonomous vehicle finds itself in emergency situations, which usually occur in a short time horizon and require large actuator inputs, together with highly nonlinear tyre cornering response. In order to avoid collision while stabilising autonomous vehicle under dynamic driving situations at handling limits, this paper proposes a novel emergency steering control strategy based on hierarchical control architecture consisting of decision-making layer and motion control layer. In decision-making layer, a dynamic threat assessment model continuously evaluates the risk associated with collision and destabilisation, and a path planner based on kinematics and dynamics of vehicle system determines a collision-free path when it suddenly encounters emergency scenarios. In motion control layer, a lateral motion controller considering nonlinearity of tyre cornering response and unknown external disturbance is designed using tyre lateral force estimation-based backstepping sliding-mode control to track a collision-free path, and to ensure the robustness and stability of the closed-loop system. Both simulation and experiment results show that the proposed control scheme can effectively perform an emergency collision avoidance manoeuvre while maintaining the stability of autonomous vehicle in different running conditions.     

Combined emergency braking and turning of articulated heavy vehicles

‘Slip control’ braking has been shown to reduce the emergency stopping distance of an experimental heavy goods vehicle by up to 19%, compared to conventional electronic/anti-lock braking systems (EBS). However, little regard has been given to the impact of slip control braking on the vehicle’s directional dynamics. This paper uses validated computer models to show that slip control could severely degrade directional performance during emergency braking. A modified slip control strategy, ‘attenuated slip demand’ (ASD) control, is proposed in order to rectify this. Results from simulations of vehicle performance are presented for combined braking and cornering manoeuvres with EBS and slip control braking with and without ASD control. The ASD controller enables slip control braking to provide directional performance comparable with conventional EBS while maintaining a substantial stopping distance advantage. The controller is easily tuned to work across a wide range of different operating conditions.     

An adaptive integrated algorithm for active front steering and direct yaw moment control based on direct Lyapunov method

In this article, an adaptive integrated control algorithm based on active front steering and direct yaw moment control using direct Lyapunov method is proposed. Variation of cornering stiffness is considered through adaptation laws in the algorithm to ensure robustness of the integrated controller. A simple two degrees of freedom (DOF) vehicle model is used to develop the control algorithm. To evaluate the control algorithm developed here, a nonlinear eight-DOF vehicle model along with a combined-slip tyre model and a single-point preview driver model are used. Control commands are executed through correction steering angle on front wheels and braking torque applied on one of the four wheels. Simulation of a double lane change manoeuvre using Matlab^®/Simulink is used for evaluation of the control algorithm. Simulation results show that the integrated control algorithm can significantly enhance vehicle stability during emergency evasive manoeuvres on various road conditions ranging from dry asphalt to very slippery packed snow road surfaces.     

A Fuzzy Logic Direct Yaw-Moment Control System for All-Wheel-Drive Electric Vehicles

Summary In-wheel-motors are revolutionary new electric drive systems that can be housed in vehicle wheel assemblies. Such E-wheels permit packaging flexibility by eliminating the central drive motor and the associated transmission and driveline components, including the transmission, the differential, the universal joints and the drive shaft. Apart from many advantages of such a system, unequalled independent wheel control allows vehicle dynamic improvement to assist the driver in enhancing cornering and straight-line stability on slippery roads and in adverse ground conditions. In this paper a Fuzzy logic driver-assist stability system for all-wheel-drive electric vehicles based on a yaw reference DYC is introduced. The system assists the driver with path correction, thus enhancing cornering and straight-line stability and providing enhanced safety. A feed-forward neural network is employed to generate the required yaw rate reference. The neural net maps the vehicle speed and the steering angle to give the yaw rate reference. The vehicle true speed is estimated using a multi-sensor data fusion method. Data from wheel sensors and an embedded accelerometer are fed into an estimator, where a Fuzzy logic system decides which input is more reliable. The efficiency of the proposed system is approved by conducting a computer simulation. The proposed control system is an effective and easy to implement method to enhance the stability of all-wheel-drive electric vehicles.     

A Fuzzy Logic Direct Yaw-Moment Control System for All-Wheel-Drive Electric Vehicles

Summary In-wheel-motors are revolutionary new electric drive systems that can be housed in vehicle wheel assemblies. Such E-wheels permit packaging flexibility by eliminating the central drive motor and the associated transmission and driveline components, including the transmission, the differential, the universal joints and the drive shaft. Apart from many advantages of such a system, unequalled independent wheel control allows vehicle dynamic improvement to assist the driver in enhancing cornering and straight-line stability on slippery roads and in adverse ground conditions. In this paper a Fuzzy logic driver-assist stability system for all-wheel-drive electric vehicles based on a yaw reference DYC is introduced. The system assists the driver with path correction, thus enhancing cornering and straight-line stability and providing enhanced safety. A feed-forward neural network is employed to generate the required yaw rate reference. The neural net maps the vehicle speed and the steering angle to give the yaw rate reference. The vehicle true speed is estimated using a multi-sensor data fusion method. Data from wheel sensors and an embedded accelerometer are fed into an estimator, where a Fuzzy logic system decides which input is more reliable. The efficiency of the proposed system is approved by conducting a computer simulation. The proposed control system is an effective and easy to implement method to enhance the stability of all-wheel-drive electric vehicles.