Brushless PM machine drive in electric and hybrid electric vehicles based on the space vector current control

This paper presents a space vector current controller for a brushless permanent magnet motor in electric and hybrid electric vehicles. The proposed current controller selects space vectors based on the sector selection under a three-level hysteresis comparator to decrease the current ripple. The proposed approach can improve the performance of a brushless PM drive such as the average switching frequency and the total harmonic distortion (THD) compared with the conventional hysteresis current control. The experiment is performed first to verify the proposed control. Then, the method is implemented in a hybrid electric vehicle simulation model with standard driving cycles based on the control strategy to evaluate the drive performance in the vehicle system. The experimental and simulation results indicate that the presented control can improve the performance of the brushless PM machine drive.     

纯电动汽车MCU母线电流采样电路及故障机制

设计一种纯电动汽车电机控制器直流母线电流采样电路,在此基础上提出一种电流采样故障的故障处理方法,该方法根据驱动系统当前状态实现了对电机控制器输入端直流母线电流的有效估算。当发生电机控制器直流母线电流采样回路故障后,利用估算值继续保证整车控制逻辑的正常执行,在保证安全行车的前提下,尽可能对驾驶员的驾驶感受进行保护。最后通过实车对该采样电路及故障机制进行验证。     

Tire–road friction coefficient estimation based on the resonance frequency of in-wheel motor drive system

In this paper, a resonance frequency-based tire–road friction coefficient (TRFC) estimation method is proposed by considering the dynamics performance of the in-wheel motor drive system under small slip ratio conditions. A frequency response function (FRF) is deduced for the drive system that is composed of a dynamic tire model and a simplified motor model. A linear relationship between the squared system resonance frequency and the TFRC is described with the FRF. Furthermore, the resonance frequency is identified by the Auto-Regressive eXogenous model using the information of the motor torque and the wheel speed, and the TRFC is estimated thereafter by a recursive least squares filter with the identified resonance frequency. Finally, the effectiveness of the proposed approach is demonstrated through simulations and experimental tests on different road surfaces.     

Advanced permanent magnet motor drive modeling for automotive application under matlab/simulink environment

This paper proposes an advanced permanent magnet (PM) motor drive modeling for dynamic analysis of automotive control systems with PM motor drives. To enhance the reusability of the proposed PM motor drive model, each component is modeled in an object-oriented manner according to the physical partitioning of a real drive system, and userfriendly and well-organized interfaces are also proposed. These characteristics enable this model to be used as a kind of a programming library. A multi-level modeling strategy is also proposed, which helps make a compromise between model accuracy and simulation speed without structural modification of the system model. The model and modeling strategy developed allow for a comprehensive analysis of each component and dynamic analysis of the total system. System simulation results show the practical effectiveness of the proposed modeling strategy.     

Torque ripple minimization control of permanent magnet synchronous motors for EPS applications

This paper identifies a control method used to reduce torque ripple of a permanent magnet synchronous motor (PMSM) for an electric power steering (EPS) system. NVH (Noise Vibration Harshness) is important for safe and convenient driving. Vibration caused by motor torque is a problem in column type EPS systems. Maintaining a very low torque ripple is one solution that allows for smoother steering. Theoretically, it is possible to design and drive the motor without torque ripple. However, in reality, a PMSM system torque ripple is caused by the motor itself (saturation in the iron core and EMF distortion) and the imperfect driver. This paper analyzes torque ripple of a PMSM system, and an advanced PMSM control method for the column typed EPS system is presented. Results of the analysis indicate that the compensation current is needed in order to minimize torque ripple when a PMSM is driven.     

探究新能源汽车的驱动电机系统

驱动电机系统存在驱动功能,为新能源汽车的一个重要组成结构,能够确定新能源汽车具体驾驶方向。为改善驱动电机系统对应运转情况,减少新能源汽车对应能耗,应充分了解新能源汽车对应驱动电机系统状况。本文主要分析新能源汽车涉及驱动电机系统对应现状情况,总结驱动电机系统具体类型状况,了解驱动电机系统详细驱动方式,进而促使新能源汽车相关驱动电机系统的推广运用。     

隧道掘进机刀盘驱动多电机同步自适应耦合控制研究

为解决隧道掘进机运行过程中刀盘驱动系统各电机受力不均衡导致的部件损坏或系统故障的问题，对刀盘驱动系统结构及控制模式进行分析，建立电机矢量控制模型，提出一种改进的刀盘驱动耦合控制结构。该结构一方面可以增加从电机给定转速选择功能，消除起动阶段延时引起的同步误差； 另一方面，可以通过转速补偿耦合策略缩小电机之间的转速差。在控制方法上，设计神经网络PI控制器来控制各个电机的转速，使控制系统能够根据载荷的变化自适应调整控制参数，提高控制精度。最后，通过建立Simulink仿真模型，对比自适应耦合控制与主从控制、并行控制的同步效果。结果表明，所提出的自适应耦合控制方法能够使控制中的各个环节相互配合，可达到较好的控制性能和响应转速。     

新能源汽车驱动电机制造层面的NVH分析和优化研究

NVH(Noise Vibration Harshness噪音振动平顺性)是新能源汽车行业衡量驱动电机的设计水平和制造质量的重要指标。为了从制造过程来分析和优化驱动电机的NVH性能,提升量产电机产品的制造质量,本文结合六西格玛DMAIC质量体系方法,应用到车用驱动电机产品的实际量产制造中,进行了制造产线中NVH相关的MSA(测量系统分析),利用FTA(故障树分析)得到了影响电机制造NVH的相关变量,通过相关性分析方法和最佳子集回归法得到了影响制造NVH的关键因素,优化并将改善点加入了产线NVH控制计划。本研究对于提升车用驱动电机的制造质量水平及建立车用驱动电机制造NVH开发体系具有重要意义。     

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.     

分布式驱动电动汽车转矩节能优化分配

为了提高分布式驱动电动汽车的经济性和续航里程,对4个轮毂电机驱动转矩优化分配问题进行研究。通过轮毂电机台架试验得到轮毂电机的驱动效率特性,分析转矩优化分配实现节约整车能耗的可行性;建立侧重提高电机效率的目标函数,使电机转矩处于电机效率Map图中的高效区;建立侧重提高电机响应速度的目标函数,减小转矩分配瞬间电流波动过大带来的能耗;基于模糊理论设计以电机效率为变量的权重函数,实时调节权重来协调2种目标函数,提出一种转矩节能优化分配方法,得到最优的轴间转矩分配系数。在后轴驱动、平均分配、优化分配3种分配方式下进行整车能耗的ECE城市循环工况对比仿真分析。结果表明：提出的节能优化分配方法通过实时优化驱动电机的转矩,避免了电机工作在转矩过大和过小的低效区,提高了整个驱动系统的能量利用率,相比于后轴驱动和平均分配整车能耗效率提高了5.91%和10.54%;实车试验验证了转矩节能优化分配算法的节能效果,优化分配相比另外2种分配方式整车能耗效率分别提高了3.66%和8.58%。     

自动变速器电子换挡系统挡位位置自学习控制算法设计

电子换挡系统 （Electronic Transmission Range Select System，ETRS） 的控制精度受自动变速器、换挡执行机构的零件自身误差及装配误差的影响，驻车挡、倒车挡、空挡、前进挡各挡位的理论位置与实际装配结果不可能完全匹配，这不仅会影响电子换挡系统的控制精度，而且长期使用后可能存在换挡功能失效的潜在风险。针对上述问题，研究设计了电子换挡系统相关硬件架构、挡位位置识别方法及关键自学习控制算法。控制算法集成直流电机匀速控制、H桥驱动电流数据读取、槽底挡位位置识别、多轮次槽底扫描迭代及挡位位置校验。仿真及实车试验表明，设计的挡位位置识别方法能够实现误差不大于0.15°，自学习控制算法能够实现实车试验大数据下均值与理论角度位置差距不大于0.3°，同时保证100%成功率，满足电控换挡系统长期工作的准确性及耐久性要求。 .     

Fault detection and diagnosis of the electromechanical brake based on observer and parity space

In the future, the conventional hydraulic brake system in automobiles will be removed and replaced by an electrically operated brake system called brake-by-wire. The brake-by-wire units, such as the EMB (Electro-Mechanical Brake), provide better braking performance by directly controlling the brake motor and are environmentally friendly because they do not use hydraulic fluid. For implementation of the EMB systems, reliable and robust fault detection and diagnosis methods become increasingly important. In this study, a sensor fault diagnosis method is proposed with parity space and observer approaches to detect faults in the motor current sensor, speed (or position) sensor and clamping force sensor. The proposed method is verified through a closed-loop simulation using Matlab/Simulink, and the simulation result is compared with the HILS bench test results.     

基于功能安全的分布式驱动电动汽车前轮失效补偿控制

分布式驱动电动汽车可以实现四轮转矩分配和差动转向,提升整车的动力学控制性能和经济性,但是四轮转矩独立可控的特点也对功能安全提出挑战。当前轮单侧电机出现执行器故障失效情况时,不仅会产生附加横摆力矩降低车辆安全性,差动转向功能的存在还会使车辆严重偏航。基于此,在设计分布式驱动-线控转向一体化底盘的基础上,基于功能安全提出一种分布式驱动电动汽车前轮失效补偿控制策略。首先建立分布式驱动失效动力学模型,分析前轮失效对车辆状态的影响机理,发现单一的驱动转矩截断控制无法满足车辆状态修正需求;其次设计一套备用的线控转向结构,通过变截距滑模控制算法提高切换状态下线控转向系统的转角跟踪性能,并用台架试验验证跟踪的准确性;然后设计自适应失效诊断观测器实时诊断驱动系统的电机故障,在将对应轮进行驱动转矩截断后,通过模型预测控制算法对车轮转矩重新分配实现纵向和侧向的状态跟踪;最后通过仿真和实车试验验证所提失效补偿控制策略的有效性和可用性。研究结果表明：分布式驱动电动汽车前轮单侧电机失效后,备用的线控转向系统能及时矫正前轮转角,所提出的失效补偿控制策略能够快速恢复车辆的稳定性和路径跟踪能力。     

一种新型柴油机电子调速器测控系统的研制

介绍了一种新型柴油机电子调速器测控系统的设计。硬件方面设计了电机驱动、转速采集和信号倍频等电路;软件方面运用Visual Basic 6.0设计了PCI—1716数据采集卡与工控机的接口程序,编写了电机控制算法,开发了人机控制界面。通过对Heinzmann电子调速器的试验,从调速器的静态、动态指标以及测控系统的模拟性等方面,验证该测控系统的实用性。     

驱动电机技术挺起我国电动汽车的脊梁

针对节能减排促进电动汽车产业的发展,论述了电动汽车驱动电动机的类型和基本要求,分析了驱动电机控制系统的核心技术,阐述了我国电动汽车驱动电机行业发展现状与挑战,同时指出了我国电动汽：车驱动电动机系统的发展趋势。     

Adaptive Control of 4WS System by Using Neural Network

An adaptive control system of the model following type is proposed for drive motion control of a four wheel steering (4WS) car with using neural network (NN) which has mastered nonlinear friction force between tire and road surface. A model of one rigid body is adopted which represents appropriately two kinds of car motion caused by steering action, namely the lateral displacement and the yawing rotation, and an equation of motion is described in a simplified form to make a system equation for motion control possible. Nonlinear relation between the cornering force of tire and the slip angle is obtained by numerical analysis with the tire model proposed by E. Fiala, taking friction coefficient and car speed as the parameters. The result is used as the teaching signal for NN. Three NN are used in the control system composed of both the feed-forward and the feedback circuits in order to realize adaptive control. Validity and usefulness of the proposed adaptive control system with NN are verified by three kinds of computer simulation.     

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。     

模糊PID控制的电动汽车再生制动系统变换器的研究

提出了利用超级电容作为储能元件实现电动汽车再生制动的能量回收方案,分析了电动汽车控制系统的双向DC/DC变换器和电机驱动器的驱动降压电路、制动升压电路,设计了该控制系统的模糊自整定PID控制器。通过仿真研究表明,在车辆驱动降压变换时,模糊自整定PID控制的超级电容器在150 A左右的大电流放电情况下,超级电容仍能维持2.5 s的指定电压输出,车辆在额定功率下工作,通过降压变换,超级电容储存的能量迅速供给电机,有效提高了驱动电流,改善了起动及加速性能,有效增加了续驶里程。在制动升压变换时,模糊自整定PID控制的超级电容器电流基本跟随指令值上下波动,超级电容电压从120 V不断上升,使得该电容器的储能能力得到充分利用,实现了高水平的能量回收。     

Adaptive Control of 4WS System by Using Neural Network

SUMMARY

An adaptive control system of the model following type is proposed for drive motion control of a four wheel steering (4WS) car with using neural network (NN) which has mastered nonlinear friction force between tire and road surface. A model of one rigid body is adopted which represents appropriately two kinds of car motion caused by steering action, namely the lateral displacement and the yawing rotation, and an equation of motion is described in a simplified form to make a system equation for motion control possible. Nonlinear relation between the cornering force of tire and the slip angle is obtained by numerical analysis with the tire model proposed by E. Fiala, taking friction coefficient and car speed as the parameters. The result is used as the teaching signal for NN. Three NN are used in the control system composed of both the feed-forward and the feedback circuits in order to realize adaptive control. Validity and usefulness of the proposed adaptive control system with NN are verified by three kinds of computer simulation.