Controller design for vehicle stability enhancement

A Vehicle Dynamics Control (VDC) system is developed for tracking desired vehicle behavior. The cascade structure of control system consists of yaw moment major controller and wheel slip minor controller. The Linear Quadratic Regulator (LQR) theory is exploited for yaw moment controller and the sliding mode theory is applied for wheel slip controller design. The use of yaw moment control was investigated by regulating the wheel slip ratio for improving handling and stability of vehicle. The performance of the control system is evaluated under various emergency maneuvers and road conditions through pure computer simulations and Hardware In-the-Loop Simulation (HILS) system. The results indicate the proposed system can significantly improve vehicle stability for active safety.     

基于模糊控制的分布式电动车辆横摆力矩研究

为提高多轮分布式电驱动车辆在不同工况下的操纵稳定性,设计了一种基于直接横摆力矩控制的分层控制策略。上层以横摆角速度和质心侧偏角为控制变量,采用模糊控制进行目标运动状态跟踪,决策出所需要的横摆力矩。下层按设计的规则进行转矩分配。应用TruckSim和Matlab/Simulink建立车辆和控制器模型,分别在高、低附着等工况下进行联合仿真。仿真结果表明,设计的模糊控制方法能对车辆目标状态进行良好跟踪,相较于无控制状态能够提高车辆的操纵稳定性。     

Integrated vehicle dynamics management for distributed‐drive electric vehicles with active front steering using adaptive neural approaches against unknown nonlinearity

This paper proposes a new integrated vehicle dynamics management for enhancing the yaw stability and wheel slip regulation of the distributed‐drive electric vehicle with active front steering. To cope with the unknown nonlinear tire dynamics with uncertain disturbances in integrated control problem of vehicle dynamics, a neuro‐adaptive predictive control is therefore proposed for multiobjective coordination of constrained systems with unknown nonlinearity. Unknown nonlinearity with unmodeled dynamics is modeled using a random projection neural network via adaptive machine learning, where a new adaptation law is designed in premise of Lyapunov stability. Given the computational efficiency, a neurodynamic method is extended to solve the constrained programming problem with unknown nonlinearity. To test the performance of the proposed control method, simulations were conducted using a validated vehicle model. Simulation results show that the proposed neuro‐adaptive predictive controller outperforms the classical model predictive controller in tracking nominal wheel slip ratio, desired vehicle yaw rate and sideslip angle, showing its significance in vehicle yaw stability enhancement and wheels slip regulation.     

横摆力矩和主动前轮转向结合的车辆横向稳定性模糊控制仿真

提出一种基于横摆力矩和主动前轮转向相结合的车辆横向稳定性控制方法,以横摆角速度和侧偏角为控制目标,利用前馈补偿和模糊控制产生横摆力矩和附加的前轮转角,通过控制制动力的分配以及对转向角的修正,使车辆转向行驶时的横摆角速度和侧偏角很好地跟踪参考模型.对转向轮阶跃输入和正弦输入两种工况分别进行了仿真研究,采用横摆力矩和主动前轮转向相结合控制方法,车辆转向时的瞬态及稳态响应优于单独的横摆力矩控制,表明该方法能有效地控制车辆横摆角速度和侧偏角,提高车辆转向时的横向稳定性,同时能有效地减轻驾驶员操纵负担.     

Adaptive neuro-fuzzy wheel slip control

Due to complex and nonlinear dynamics of a braking process and complexity in the tire–road interaction, the control of automotive braking systems performance simultaneously with the wheel slip represents a challenging problem. The non-optimal wheel slip level during braking, causing inability to achieve the desired tire–road friction force strongly influences the braking distance. In addition, steerability and maneuverability of the vehicle could be disturbed. In this paper, an active neuro-fuzzy approach has been developed for improving the wheel slip control in the longitudinal direction of the commercial vehicle. The dynamic neural network has been used for prediction and an adaptive control of the brake actuation pressure, during each braking cycle, according to the identified maximum adhesion coefficient between the wheel and road surface. The brake actuation pressure was dynamically adjusted on the level that provides the optimal level of the longitudinal wheel slip vs. the brake pressure selected by driver, the current vehicle speed, the brake interface temperature, vehicle load conditions, and the current value of longitudinal wheel slip. Thus the dynamic neural network model operates (learn, generalize and predict) on-line during each braking cycle, fuzzy logic has been integrated with the neural model as a support to the neural controller control actions in the case when prediction error of the dynamic neural model reached the predefined value. The hybrid control approach presented here provided intelligent dynamic model – based control of the brake actuation pressure in order to keep the longitudinal wheel slip on the optimum level during a braking cycle.     

液压混合动力履带车辆联合制动模糊控制

针对液压混合动力履带车辆联合制动系统,为了实现制动过程平稳性,提出了基于制动力分配原则的模糊控制策略.首先在MATLAB中建立了能量再生制动系统和机械制动系统以及车辆动力学仿真模型,然后设计了以制动力分配系数为控制变量的联合制动模糊控制器,给出了模糊控制规则,建立了控制系统仿真模型,并在不同制动强度条件下对车辆制动过程进行仿真.仿真结果表明,联合制动模糊控制系统能够有效回收制动能量,同时与PID控制相比明显改善和提高了履带车辆制动过程稳定性.     

A novel integrated control framework of AFS,ASS, and DYC based on ideal roll angle to improve vehicle stability

The current research on vehicle stability control mainly focuses on following the ideal yaw rate and sideslip angle, without considering the potential of ideal roll angle in improving the vehicle stability. In addition, the mutation of tire-road friction coefficient promotes a great challenge to the stability control. To improve the vehicle stability, in this study, firstly, the three-dimensional stability region of “lateral speed-yaw rate-roll angle” was studied, and a method to determine the ideal roll angle was proposed. Secondly, a novel integrated control framework of AFS, ASS, and DYC based on ideal roll angle was proposed to actively control the front tire slip angles, suspension forces, and motor torques: In the upper-level controller, model predictive control and tire force distribution algorithm were used to obtain the optimal four-tire longitudinal forces, front tire lateral forces and additional roll moment under constraints; In the lower-level controller, the upper virtual target was realized by the optimal allocation algorithm of actuators and the tire slip controller. Finally, the proposed control framework was verified on the varied-µ road. The results indicated that compared with the two existing control strategies, the proposed framework can significantly improve the vehicle following performance and stability.     

后轴双电机扭矩矢量控制研究

车辆的横摆响应受到转向系统、悬架系统、制动系统及驱动系统影响,传统车辆主要以转向输入进行主动控制,随着线控底盘的发展,ESC、后轮转向、扭矩矢量等技术逐步参与到车辆横摆的主动控制中;相对于ESC以制动力差产生横摆力矩,扭矩矢量可在不降低总驱动力的前提下产生横摆力矩,不会引起车辆的制动效应;通过后轴双电机扭矩矢量控制（TVC）产生主动横摆力矩,旨在改善车辆横摆响应,TVC采用前馈与反馈结合控制,基于二自由度车辆模型、目标稳态增益K及横摆角速度-速度修正因子K1建立目标横摆角速度;利用车辆模型逆函数计算横摆力矩前馈值,PID计算横摆力矩反馈值,总横摆力矩转换得到左右车轮纵向力调整量;纵向力调整量与驱动力分量叠加获得左右轮总纵向力;左右轮驱动力过大时可能会受到滑移率、电机扭矩等限制,为保证横摆力矩偏差在要求范围内,需要根据限制情况对左右轮纵向力进行调整;通过仿真验证,TVC可明显改变车辆横摆响应     

An MPC-based manoeuvre stability controller for full drive-by-wire vehicles

Aiming at the actuator time delay caused by the drive-by-wire technology, a novel manoeuvre stability controller based on model predictive control is proposed for full drive-by-wire vehicles. Firstly, the future vehicle dynamics are predicted by a two-degree-of-freedom vehicle model with input delay. Secondly, in order to prevent the vehicle from destabilizing due to excessive side slip angles, the determined ideal yaw rate and side slip angle are tracked simultaneously by optimizing the front wheel angle and additional yaw moment. Moreover, in order to improve the trajectory tracking ability, a side slip angle constraint determined by phase plane stability boundaries is added to the cost function. The results of Matlab and veDYNA co-simulation show that the regulated yaw rate can track the reference value well and the side slip angle decreases. Meanwhile, the trajectory tracking ability is improved obviously by compensating the time delay.     

Yaw Moment Control Strategy for Four Wheel Side Driven EV

When four wheel side driven EV travals in steering or changes lanes in high speed, the vehicle is easy to side-slip or flick due to the difference of wheel hub motor and a direct effect of vehicle nonlinear factors on vehicle yaw motion, which would affect vehicle handling and stability seriously. To solve this problem, a joint control strategy, combined with the linear programming algorithm and improved sliding mode algorithm, which combines the exponential reaching law and saturation function was proposed. Firstly, the vehicle dynamics model and the reference model according with the structure and driving characteristics of four wheel side driven EV were set up. Then, introduced the basic method of the improved sliding mode variable structure control and complete the sliding mode variable structure controller design basic on vehicle sideslip angle and yaw velocity.The controller accomplish optimal allocation of vehicle braking force through a linear programming algorithm, according to yaw moment produced by the vehicle motion state. Single lane driving simulation results show that the proposed control strategy can not only control vehicle sideslip angle and yaw velocity well, but also accomplish good controlling of the vehicle yaw moment, so as to significantly improve the handling and stability of vehicle.     

Practical active traction control for independent-wheel-drive electric vehicle based on slip-ratio threshold determination

The traditional traction control system (TCS) based on hydraulic braking only works when the wheels are slipping, which will cause the problem of slow response to extreme slip. In addition, the TCS of four-wheel-independent-drive electric vehicle (4WIDEV) is often based on road adhesion characteristics identification or optimal slip ratio identification to implement active control, which is difficult to achieve in engineering. Aiming at this problem, a practical active TCS is proposed in this paper. Firstly, according to the wheel slip state of the front and rear axles, the dynamic transfer of torque between axles is realized to maintain the vehicle propulsion power. Second, the adhesion conditions between road and tire are classified, and two sets of target slip ratio thresholds are formulated for high and low adhesion pavement, respectively. Then the current road adhesion coefficient is estimated by using the advantage that the in-wheel motor torque can be obtained in real-time. Thirdly, the overall framework of the control strategy is established, the logic threshold control algorithm is adopted for tracking the wheel target slip ratio. Finally, the simulation results show that the proposed active TCS can improve the vehicle power and avoid excessive wheel slipping.     

四轮独立驱动电动汽车单轮失效稳定性控制

为了解决四轮独立驱动电动汽车驱动系统失效时的转矩分配问题,提出了一种基于规则的驱动力控制分配策略以保证车辆在出现单轮失效情况下的稳定性和动力性.控制器采用双层控制,包括上层控制和下层控制.在上层控制中,根据驾驶员的输入与车辆状态,采用滑模控制理论计算出控制横摆角速度和质心侧偏角的附加横摆力矩.在下层控制中,根据驱动电机...     

Lateral motion control for four-wheel-independent-drive electric vehicles using optimal torque allocation and dynamic message priority scheduling

In this paper, the vehicle lateral motion control of four-wheel-independent-drive electric vehicles (4WID-EVs) with combined active front steering (AFS) and direct yaw moment control (DYC) through in-vehicle networks is studied. As a typical over-actuated system, a 4WID-EV requires a control allocation algorithm to achieve the generalized control efforts. In this paper, a quadratic programming (QP) based torque allocation algorithm is proposed with the advantage of equally and reasonably utilizing the tire-road friction of each wheel. It is also well known that the in-vehicle network and x-by-wire technologies have considerable advantages over the traditional point-to-point communications, and bring great strengths to complex control systems such as 4WID-EVs. However, there are also bandwidth limitations which would lead to message time-delays in in-vehicle network communications and degradation of control performance. The paper also proposes a mechanism to effectively utilize the limited network bandwidth resources and attenuate the adverse impact of in-vehicle network-induced time-delays, based on the idea of dynamic message priority scheduling. Simulation results from a high-fidelity vehicle model show that the proposed control architecture with the torque allocation algorithm and message dynamic-priority scheduling procedure can effectively improve the vehicle lateral motion control performance, and significantly reduce the adverse impact of the in-vehicle network message time-delays in the simulated maneuvers.     

Estimation of road frictional force and wheel slip for effective antilock braking system (ABS) control

The introduction of electric braking via brake‐by‐wire systems in electric vehicles) has reduced the high transportation delays usually involved in conventional friction braking systems. This has facilitated the design of more efficient and advanced control schemes for antilock braking systems (ABSs). However, accurate estimation of the tire‐road friction coefficient, which cannot be measured directly, is required. This paper presents a review of existing estimation methods, focusing on sliding‐mode techniques, followed by the development of a novel friction estimation technique, which is used to design an efficient ABS control system. This is a novel slip‐based estimation method, which accommodates the coupling between the vehicle dynamics, wheel dynamics, and suspension dynamics in a cascaded structure. A higher‐order sliding‐mode observer–based scheme is designed, considering the nonlinear relationship between friction and slip. A first‐order sliding‐mode observer is also designed based on a purely linear relationship. A key feature of the proposed estimation schemes is the inclusion of road slope and the effective radius of the tire as an estimated state. These parameters impact significantly on the accuracy of slip and friction estimation. The performance of the proposed estimation schemes are validated and benchmarked against a Kalman filter (KF) by a series of simulation tests. It is demonstrated that the sliding‐mode observer paradigm is an important tool in developing the next generation ABS systems for electric vehicles.     

Robust cascaded automatic cruise control of electric vehicles

This article focuses on automatic cruise control for electrically driven vehicles. The objective is to track a given vehicle‐velocity profile. For this type of application, the so‐called wheel slip plays a key role, as it is a measure for the force transmitted from the wheel to the road. Conventional wheel‐ slip controllers are usually activated if the absolute value of the slip exceeds pre‐assumed thresholds. Furthermore, it is distinguished between a braking and acceleration maneuver using separately designed and implemented controllers. In contrast, the proposed concept requires neither an activation strategy for the slip controller nor a distinction between braking and acceleration. The cascaded control structure is based upon adaptive‐gains super twisting sliding‐mode algorithm, and the friction force estimator is realized as a second‐order sliding‐mode observer with constant gains. The effectiveness and robustness of the proposed concept are demonstrated in numerical simulations using a complex multibody vehicle model. Copyright © 2015 John Wiley & Sons, Ltd.     

Disturbance Observer Based Control for Four Wheel Steering Vehicles With Model Reference

This paper presents a disturbance observer based control strategy for four wheel steering systems in order to improve vehicle handling stability. By combination of feedforward control and feedback control, the front and rear wheel steering angles are controlled simultaneously to follow both the desired sideslip angle and the yaw rate of the reference vehicle model. A nonlinear three degree-of-freedom four wheel steering vehicle model containing lateral, yaw and roll motions is built up, which also takes the dynamic effects of crosswind into consideration. The disturbance observer based control method is provided to cope with ignored nonlinear dynamics and to handle exogenous disturbances. Finally, a simulation experiment is carried out, which shows that the proposed four wheel steering vehicle can guarantee handling stability and present strong robustness against external disturbances.      

电动汽车动力学控制研究进展

近年来随着全球资源、环境问题日益严峻,节能、环保的电动汽车得到快速发展。电动汽车采用电机驱动系统,具有转矩快速响应、易于精确测量、可实现动力分散控制、可实现制动能量回收等优点。充分挖掘并利用这些优点可显著提升车辆动力学控制性能。文中从电动汽车动力学控制运行参数的识别、动力学控制结构与方法两个角度综述了十多年来的研究成果,重点介绍了轮胎-路面接触条件识别方法、驱动防滑控制方法等。对车辆横向动力学控制,包括电子差速控制、直接横摆控制、底盘集成控制等研究现状也做了总结。最后对未来电动车辆动力学控制的发展方向作了几点展望。     

Adaptive Composite Fuzzy Dynamic Surface Control for Electro‐Hydraulic‐System,with Variable‐Supply‐Pressure

This paper presents a novel adaptive composite fuzzy dynamic surface controller for a variable‐supply‐pressure electro‐hydraulic‐system in the presence of unknown nonlinear friction effects. To avoid analytic calculation, command filters are utilized to produce certain virtual controllers and their derivatives. A fuzzy logic system is designed to approximate and compensate the unknown nonlinear friction influences of the electro‐hydraulic‐system. To achieve a precise approximation, the prediction error of a designed serial‐parallel estimation model and the compensated tracking error are both used to develop the composite adaptive law. Comparative simulation and experimental results are obtained to verify the effectiveness of the proposed control method.     

Integrated Dynamics Control and Energy Efficiency Optimization for Overactuated Electric Vehicles

A large number of studies have been conducted on the dynamics control of electric vehicles or on the optimization of their energy efficiency but few studies have looked at both of these together. In this study, an integrated dynamics control and energy efficiency optimization strategy is proposed for overactuated electric vehicles, where the control of both longitudinal and lateral dynamics is dealt with while the energy efficiency is optimized. First, considering the trade‐off between control performance and energy efficiency, criteria are defined to categorize the vehicle motion status as linear pure longitudinal motion and non‐linear motion or turning motion. Then different optimization targets are developed for different motion status. For the pure linear longitudinal motion and cornering motion, the energy efficiency and vehicle dynamics performance are equally important and a trade‐off control performance between them needs to be achieved. For the non‐linear turning motion, vehicle handling and stability performance are the primary concerns, and energy efficiency is a secondary target. Based on the defined targets, the desired longitudinal and lateral tyre forces and yaw moment are then optimally distributed to the wheel driving and steering torques. Finally numerical simulations are used to verify the effectiveness of the proposed strategies. The simulation results show that the proposed strategies can provide good dynamics control performance with less energy consumption.     

车辆直接横摆力矩的预测控制研究

针对车辆高速过弯时发生的侧滑问题,将预测控制运用于汽车ESP控制系统中,以2自由度车辆模型为预测内部模型,以车辆直接横摆力矩为输出作用于车轮来控制整车的行驶状态。结合Matlab/Simulink建立的七自由度整车模型以及轮胎模型对所设计的ESP控制器进行分析调整。实验结果表明,预测控制器能很好地控制汽车的横摆角速度和限制质心侧偏角,提高了汽车的稳定性和安全性。