电动汽车复合制动控制研究现状综述

电动汽车复合制动由电机再生制动与机械摩擦制动两部分构成,其控制性能直接影响车辆的能量利用效率、制动安全性以及舒适性。围绕静态制动转矩分配控制、动态复合制动协调控制、制动换挡控制、智能辅助驾驶中的复合制动控制4个方面的研究现状与关键技术展开综述,并对复合制动控制未来研究方向进行了展望。对文献的梳理分析表明：制动转矩分配决定着复合制动系统能量回收能力与车辆制动稳定性,基于规则的分配策略面对复杂多变工况自适应性欠佳,而基于优化的分配策略各方面性能表现良好,但需要兼顾控制实时性与优化效果;利用电机响应迅速与控制精确的优势完成复合制动协调控制,能够提升制动模式切换过渡工况与紧急制动工况的控制性能,改善驾驶舒适性;制动过程中实施合理换挡可以进一步提升能量回收效率,同时通过补偿控制解决换挡过程中动力中断和转矩冲击等问题,保证换挡平顺性;随着电动汽车智能化和网联化发展,复合制动控制与驾驶人辅助系统相结合有助于在保证系统功能的同时实现能量回收效益最大化。     

双电机驱动电动汽车再生制动控制策略研究

以能量回收最大化为目标,提出一种双电机驱动电动汽车再生制动模糊控制策略,通过分析再生制动原理,考虑ECE法规、理想制动力分配曲线、电机、电池功率等约束,利用模糊控制理论确定电机制动所占比例,在保证制动方向稳定的前提下,合理分配前、后轴制动力,协调机电复合制动力。利用MATLAB/Simulink对控制策略进行不同工况下的仿真和硬件在环试验验证,结果表明:所设计的控制策略可实现机电复合制动系统的协调工作,有效延长续驶里程。     

电动汽车机电复合制动力分配策略

对某电动汽车机电复合制动系统进行了研究,制定了电动汽车机电复合制动系统的结构方案。依据ECE-R13法规与最大电机制动力限制,确定机电解耦门限值,对小强度制动、中强度制动及紧急制动3种不同工况分别制定了不同的再生制动与液压制动控制策略,并进行仿真与试验验证。结果表明,在小强度制动时电机可满足驾驶员的需求制动力,并且能量回收率能够达到25%;在中强度制动时电机以最大制动力进行制动并且在最大回收能量的同时能够使该系统满足制动性能,能量回收率能够达到74%;在紧急制动时为了制动安全应迅速将电机制动力撤出。该复合制动系统能够有效地吸收再生制动能量,同时也能满足车辆的制动性能。     

基于I线制动力分配的四驱纯电动汽车制动能量回收策略的研究EI北大核心CSCD

针对具有双轴双电机四驱结构的电动汽车,设计了一种基于I线制动力分配策略。该策略在制动时,前后轴制动力按照I线分配,前后电机同时回收能量,既发挥了制动能量回收潜力,又保证了制动稳定性。仿真结果表明,该策略能回收更多的能量,制动力分配曲线与I线相吻合,保证了制动稳定性,也验证了该策略的有效性。     

分布式驱动电动汽车复合制动系统转矩分配控制策略仿真

针对分布式驱动电动汽车,提出了一种复合制动系统控制策略。采用分层的制动转矩分配控制结构,上层控制器采用滑模控制策略,对目标纵向力和横摆力矩进行求解,以满足车辆在制动时制动效能和制动稳定性的要求;下层控制器采用加权最小二乘控制,对四轮液压制动转矩和电机制动转矩进行分配,通过增大电机制动力分配的权值达到能量回收的最大化,并采用有效集算法完成目标函数的求解。在此基础上,在Simulink中建立了7自由度整车动力学模型,在对开路面的工况下进行了仿真分析,结果表明:所制定的控制策略能满足要求,在保证车辆制动稳定性的同时,最大限度回收制动能量。     

一种电动汽车制动能量回收系统研究

文章以某款纯电动车制动能量回收系统为研究对象,首先,设计一种电液助力系统,阐述其结构方案和工作原理,接着基于该电液助力系统开展纯电动车串行制动能量回收系统设计研究,包括结构方案、控制方案、电气方案;实现在某款纯电动车产品上的搭载应用开发,结果表明,基于该电液助力系统的纯电动车能量回收系统,实现车辆在制动或减速阶段,机械-液压制动力与电机回馈制动力实时协调,最大限度地回收制动能量,并且获得较好的制动稳定性和“踏板感”,单个ECE循环工况经济性贡献率最高达28.9%。     

电动汽车复合制动系统研究现状综述

从原理、结构、特点、控制策略和制动动力学控制等方面阐述了电动汽车复合制动系统的发展现状,针对复合制动系统的3种结构型式(油门踏板型、未解耦型和解耦型)进行了对比分析,表明解耦型复合制动系统是未来复合制动系统的主要发展方向。重点分析了解耦型复合制动系统的控制策略,并且总结了正常制动和紧急制动2种工况下液压制动力和再生制动力的动态协调控制方法,最后提出复合制动对于液压制动系统的设计要求。     

混合动力车与电动车制动能量回收控制(二)电动车制动能量回收系统

液压制动与制动能量回收的组成 图6为电动汽车的液压制动和制动能量回收控制 制动能量回收电控单元,基于各车轮加速度传感器的检测输出信号判断车辆是否在良好路面状态或恶劣路面状态,只有在良好路面状态下,制动能量回收电控单元对液压制动与电机的制动能量回收实施协调控制。这是一般电动车进行能量回收制动的必要性。如果在恶劣的路况下,考虑到车辆的制动安全性,电机的电控单元及制动能量回收电控单元发出指令,逐步限制制动能量回收,直至禁止,     

混合动力汽车回馈制动与防抱死制动协调鲁棒控制

提出了一种并联式混合动力汽车防抱死制动系统(ABS)和能量回馈制动的协调控制策略。针对防抱死制动系统的强非线性和时变特征,设计了基于滑移率切换面的ABS滑模变结构控制器。为削弱传统滑模控制中的颤振和补偿模型的不确定性,采用指数趋近率方法来改善滑模运动段的动态品质和鲁棒性;能量回馈制动系统中,电池SOC、电机转速和制动强度等动态参数的影响较大,因此,采用T-S模糊逻辑控制策略动态调节电机制动转矩来提高制动能量的回收率。在Matlab/Simulink环境中建立整车制动系统模型,对所提出的协调控制策略在紧急制动和NEDC工况下进行仿真。结果表明:该策略在保证车辆制动稳定性的同时,能有效地提高制动能量的回收率,且具有较强的鲁棒性。     

纯电动汽车再生制动控制策略的研究

为了提高电动汽车制动能量的回收效率,增加汽车续驶里程,本文针对前、后轮制动力和再生制动力的分配策略进行了研究。结果表明,在制定前、后轮制动力分配策略时,采用以路面特征值识别为前提,将f线、ECE法规线和I曲线相结合的方法,根据当前路面的附着系数选择不同的控制策略,可使汽车在获得较大制动力的同时确保制动的方向稳定性;在制定再生制动力分配策略时,根据车辆实时工况,采用模糊控制的方法分配驱动轮上的再生制动力,可提高制动能量的回收效率。建立了再生制动控制策略的仿真模型,并在CYC_1015和CYC_UDDS两种工况下进行模拟仿真,仿真结果表明,本文提出的控制策略比ADVISOR原车控制策略能更好地实现制动能量回收,提高了纯电动汽车的续驶里程。     

Wheel slip control with torque blending using linear and nonlinear model predictive control

Modern hybrid electric vehicles employ electric braking to recuperate energy during deceleration. However, currently anti-lock braking system (ABS) functionality is delivered solely by friction brakes. Hence regenerative braking is typically deactivated at a low deceleration threshold in case high slip develops at the wheels and ABS activation is required. If blending of friction and electric braking can be achieved during ABS events, there would be no need to impose conservative thresholds for deactivation of regenerative braking and the recuperation capacity of the vehicle would increase significantly. In addition, electric actuators are typically significantly faster responding and would deliver better control of wheel slip than friction brakes. In this work we present a control strategy for ABS on a fully electric vehicle with each wheel independently driven by an electric machine and friction brake independently applied at each wheel. In particular we develop linear and nonlinear model predictive control strategies for optimal performance and enforcement of critical control and state constraints. The capability for real-time implementation of these controllers is assessed and their performance is validated in high fidelity simulation.     

Improvement of drivability and fuel economy with a hybrid antiskid braking system in hybrid electric vehicles

When braking on wet roads, Antilock Braking System (ABS) control can be triggered because the available brake torque is not sufficient. When the ABS system is active, for a hybrid electric vehicle, the regenerative brake is switched off to safeguard the normal ABS function. When the ABS control is terminated, it would be favorable to reactivate the regenerative brake. However, recurring cycles from ABS to motor regenerative braking could occur. This condition is felt to be unpleasant by the driver and has adverse effects on driving stability. In this paper, a novel hybrid antiskid braking system using fuzzy logic is proposed for a hybrid electric vehicle that has a regenerative braking system operatively connected to an electric traction motor and a separate hydraulic braking system. This control strategy and the method for coordination between regenerative and hydraulic braking are developed. The motor regenerative braking controller is designed. Control of regenerative and hydraulic braking force distribution is investigated. The simulation and experimental results show that vehicle braking performance and fuel economy can be improved and the proposed control strategy and method are effective and robust.     

Transient switching control strategy from regenerative braking to anti-lock braking with a semi-brake-by-wire system

Regenerative braking is an important technology in improving fuel economy of an electric vehicle (EV). However, additional motor braking will change the dynamic characteristics of the vehicle, leading to braking instability, especially when the anti-lock braking system (ABS) is triggered. In this paper, a novel semi-brake-by-wire system, without the use of a pedal simulator and fail-safe device, is proposed. In order to compensate for the hysteretic characteristics of the designed brake system while ensure braking reliability and fuel economy when the ABS is triggered, a novel switching compensation control strategy using sliding mode control is brought forward. The proposed strategy converts the complex coupling braking process into independent control of hydraulic braking and regenerative braking, through which a balance between braking performance, braking reliability, braking safety and fuel economy is achieved. Simulation results show that the proposed strategy is effective and adaptable in different road conditions while the large wheel slip rate is triggered during a regenerative braking course. The research provides a new possibility of low-cost equipment and better control performance for the regenerative braking in the EV and the hybrid EV.     

基于ARM7的汽车底盘系统分层式协调控制试验研究

采用分层协调控制策略,进行了汽车电动助力转向系统和防抱死制动系统集成控制的研究.分别设计了底层控制器和上层协调控制器,底层控制器包括电动助力转向和防抱死制动两个单独的控制器,用以执行各子系统的控制任务;上层协调控制器则对两系统进行协调分析,并及时修改底层控制决策.试验结果表明,自行开发的底层控制器逻辑正确,上层协调控制器能够较好地协调两系统问的矛盾,解决了汽车在转向过程中施加紧急制动时车辆的操纵稳定性和平顺性变差的间题,使整车综合性能得到提高.     

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.     

Distributed and self-adaptive vehicle speed estimation in the composite braking case for four-wheel drive hybrid electric car

Considering the controllability and observability of the braking torques of the hub motor, Integrated Starter Generator (ISG), and hydraulic brake for four-wheel drive (4WD) hybrid electric cars, a distributed and self-adaptive vehicle speed estimation algorithm for different braking situations has been proposed by fully utilising the Electronic Stability Program (ESP) sensor signals and multiple powersource signals. Firstly, the simulation platform of a 4WD hybrid electric car was established, which integrates an electronic-hydraulic composited braking system model and its control strategy, a nonlinear seven degrees-of-freedom vehicle dynamics model, and the Burckhardt tyre model. Secondly, combining the braking torque signals with the ESP signals, self-adaptive unscented Kalman sub-filter and main-filter adaptable to the observation noise were, respectively, designed. Thirdly, the fusion rules for the sub-filters and master filter were proposed herein, and the estimation results were compared with the simulated value of a real vehicle speed. Finally, based on the hardware in-the-loop platform and by picking up the regenerative motor torque signals and wheel cylinder pressure signals, the proposed speed estimation algorithm was tested under the case of moderate braking on the highly adhesive road, and the case of Antilock Braking System (ABS) action on the slippery road, as well as the case of ABS action on the icy road. Test results show that the presented vehicle speed estimation algorithm has not only a high precision but also a strong adaptability in the composite braking case.     

分布式驱动电动汽车回馈制动失效的液压补偿控制

分布式驱动电动汽车各驱动轮转速和转矩可以单独精确控制，便于实现整车动力学控制和制动能量回馈，从而提升车辆的主动安全性和行驶经济性。但车辆在回馈制动过程中，一旦1台电机突发故障，其他电机产生的制动力矩将对整车形成附加横摆力矩，从而造成车辆失稳，此时虽可通过截断异侧对应电机制动力矩输出来保证行驶方向，但会使车辆制动力大幅衰减或丧失，同样不利于行车安全。为了解决此问题，提出并验证一种基于电动助力液压制动系统的制动压力补偿控制方法，力图有效保证整车制动安全性。以轮毂电机驱动汽车为例，首先建立了整车动力学模型以及轮毂电机模型，通过仿真验证了回馈制动失效的整车失稳特性以及电机转矩截断控制的不足；然后，建立了电动助力液压制动系统模型，并通过原理样机的台架试验验证了模型的准确性；接着，基于滑模控制算法设计了制动压力补偿控制器，并在单侧电机再生制动失效后的转矩截断控制基础上完成了液压制动补偿控制效果仿真验证；最后，通过实车试验证明了所提控制方法的有效性和实用性。研究结果表明：在分布式驱动电动汽车单侧电机再生制动失效工况下，通过异侧电机转矩截断控制和制动系统的液压主动补偿，能够使车辆快速恢复稳定行驶并满足制动强度需求。     

A practical identifier design of road variations for anti-lock brake system

Emergency brake technologies have always been a major interest of vehicle active safety-related studies. On homogeneous surfaces, traditional anti-lock brake system (ABS) can achieve efficient braking performance and maintain the handling capability as well. However, when road conditions are time variant during the braking process, or different at the bilateral wheels, braking stability performance is likely to be degraded. To address this problem and enhance ABS performances, a practical identifier of road variations is developed in this study. The proposed identifier adopts a statechart-based approach and is hierarchically constructed with a wheel layer and a full vehicle layer identifier. Based on the identification results, modifications are made to a four-phase wheel-behaviour-based ABS controller to enhance its performance. The feasibility and effectiveness of the proposed identifier in collaborating with the modified ABS controller are examined via simulations and further validated by track tests under various practical braking scenarios.     

Cooperative control of the motor and the electric booster brake to improve the stability of an in-wheel electric vehicle

A cooperative control algorithm for an in-wheel motor and an electric booster brake is proposed to improve the stability of an in-wheel electric vehicle. The in-wheel system was modeled by dividing it into motor and mechanical parts, and the electric booster brake was modeled through tests. In addition, the response characteristics of the in-wheel system and the electric booster brake were compared through a frequency response analysis. In the cooperative control, the road friction coefficient was estimated using the wheel speed, motor torque, and braking torque of each wheel, and the torque limit of the wheel to the road was determined using the estimated road friction coefficient. Based on the estimated road friction coefficient and torque limit, a cooperative algorithm to control the motor and the electric booster brake was proposed to improve the stability of the in-wheel electric vehicle. The performance of the proposed cooperative control algorithm was evaluated through a hardware-in-the-loop simulation (HILS). Furthermore, to verify the performance of the proposed cooperative control algorithm, a test environment was constructed for the anti-lock braking system (ABS) hydraulic module hardware, and the performance of the cooperative control algorithm was compared with that of the ABS by means of a HILS test.