Pedaling torque sensor-less power assist control of an electric bike via model-based impedance control

This paper proposes a method to assist human force acting on electric bike without using costly torque sensors via a model-based impedance control technique. In general, electric bikes are classified into two categories, i.e., pedelec electric bikes and throttle electric bikes. We focus on the system called a pedelec electric bike. It assists human pedaling force using the pedaling information, e.g., pedaling force or speed. To obtain the human’s pedaling information in real-time, it needs physical sensors such as a torque sensor and a velocity sensor. But, these sensors are expensive and weak against external loads. Also, since these sensors are fixed directly to the forced component in a bike system, there are the risks of damage. For these reasons, sensor-less control methods based on a disturbance observer have been studied so far. In this paper, we have proposed a pedaling torque sensor-less power assist method and have applied it to the experimental pedelec electric bike. A power assist control algorithm, designed by employing an impedance model, consists of a PI-type feedback controller, an inverse model-based feedforward controller, and a pedaling torque observer. Finally, we performed experiments and confirmed the effectiveness of a proposed power assist control method.     

A vehicle ABS adaptive sliding-mode control algorithm based on the vehicle velocity estimation and tyre/road friction coefficient estimations

A sliding-mode observer is designed to estimate the vehicle velocity with the measured vehicle acceleration, the wheel speeds and the braking torques. Based on the Burckhardt tyre model, the extended Kalman filter is designed to estimate the parameters of the Burckhardt model with the estimated vehicle velocity, the measured wheel speeds and the vehicle acceleration. According to the estimated parameters of the Burckhardt tyre model, the tyre/road friction coefficients and the optimal slip ratios are calculated. A vehicle adaptive sliding-mode control (SMC) algorithm is presented with the estimated vehicle velocity, the tyre/road friction coefficients and the optimal slip ratios. And the adjustment method of the sliding-mode gain factors is discussed. Based on the adaptive SMC algorithm, a vehicle's antilock braking system (ABS) control system model is built with the Simulink Toolbox. Under the single-road condition as well as the different road conditions, the performance of the vehicle ABS system is simulated with the vehicle velocity observer, the tyre/road friction coefficient estimator and the adaptive SMC algorithm. The results indicate that the estimated errors of the vehicle velocity and the tyre/road friction coefficients are acceptable and the vehicle ABS adaptive SMC algorithm is effective. So the proposed adaptive SMC algorithm can be used to control the vehicle ABS without the information of the vehicle velocity and the road conditions.     

Lateral handling improvement with dynamic curvature control for an independent rear wheel drive EV

The integrated longitudinal and lateral dynamic motion control is important for four wheel independent drive (4WID) electric vehicles. Under critical driving conditions, direct yaw moment control (DYC) has been proved as effective for vehicle handling stability and maneuverability by implementing optimized torque distribution of each wheel, especially with independent wheel drive electric vehicles. The intended vehicle path upon driver steering input is heavily depending on the instantaneous vehicle speed, body side slip and yaw rate of a vehicle, which can directly affect the steering effort of driver. In this paper, we propose a dynamic curvature controller (DCC) by applying a the dynamic curvature of the path, derived from vehicle dynamic state variables; yaw rate, side slip angle, and speed of a vehicle. The proposed controller, combined with DYC and wheel longitudinal slip control, is to utilize the dynamic curvature as a target control parameter for a feedback, avoiding estimating the vehicle side-slip angle. The effectiveness of the proposed controller, in view of stability and improved handling, has been validated with numerical simulations and a series of experiments during cornering engaging a disturbance torque driven by two rear independent in-wheel motors of a 4WD micro electric vehicle.     

Rear wheel torque vectoring model predictive control with velocity regulation for electric vehicles

In this paper we propose a constrained optimal control architecture for combined velocity, yaw and sideslip regulation for stabilisation of the vehicle near the limit of lateral acceleration using the rear axle electric torque vectoring configuration of an electric vehicle. A nonlinear vehicle and tyre model are used to find reference steady-state cornering conditions and design two model predictive control (MPC) strategies of different levels of fidelity: one that uses a linearised version of the full vehicle model with the rear wheels' torques as the input, and another one that neglects the wheel dynamics and uses the rear wheels' slips as the input instead. After analysing the relative trade-offs between performance and computational effort, we compare the two MPC strategies against each other and against an unconstrained optimal control strategy in Simulink and Carsim environment.     

An investigation on motor-driven power steering-based crosswind disturbance compensation for the reduction of driver steering effort

This paper describes a lateral disturbance compensation algorithm for an application to a motor-driven power steering (MDPS)-based driver assistant system. The lateral disturbance including wind force and lateral load transfer by bank angle reduces the driver's steering refinement and at the same time increases the possibility of an accident. A lateral disturbance compensation algorithm is designed to determine the motor overlay torque of an MDPS system for reducing the manoeuvreing effort of a human driver under lateral disturbance. Motor overlay torque for the compensation of driver's steering torque induced by the lateral disturbance consists of human torque feedback and feedforward torque. Vehicle–driver system dynamics have been investigated using a combined dynamic model which consists of a vehicle dynamic model, driver steering dynamic model and lateral disturbance model. The human torque feedback input has been designed via the investigation of the vehicle–driver system dynamics. Feedforward input torque is calculated to compensate additional tyre self-aligning torque from an estimated lateral disturbance. The proposed compensation algorithm has been implemented on a developed driver model which represents the driver's manoeuvreing characteristics under the lateral disturbance. The developed driver model has been validated with test data via a driving simulator in a crosswind condition. Human-in-the-loop simulations with a full-scale driving simulator on a virtual test track have been conducted to investigate the real-time performance of the proposed lateral disturbance compensation algorithm. It has been shown from simulation studies and human-in-the-loop simulation results that the driver's manoeuvreing effort and a lateral deviation of the vehicle under the lateral disturbance can be significantly reduced via the lateral disturbance compensation algorithm.     

Stability enhancement and fuel economy of the 4-wheel-drive hybrid electric vehicles by optimal tyre force distribution

In this paper, vehicle stability control and fuel economy for a 4-wheel-drive hybrid vehicle are investigated. The integrated controller is designed within three layers. The first layer determines the total yaw moment and total lateral force made by using an optimal controller method to follow the desired dynamic behaviour of a vehicle. The second layer determines optimum tyre force distribution in order to optimise tyre usage and find out how the tyres should share longitudinal and lateral forces to achieve a target vehicle response under the assumption that all four wheels can be independently steered, driven, and braked. In the third layer, the active steering, wheel slip, and electrical motor torque controllers are designed. In the front axle, internal combustion engine (ICE) is coupled to an electric motor (EM). The control strategy has to determine the power distribution between ICE and EM to minimise fuel consumption and allowing the vehicle to be charge sustaining. Finally, simulations performed in MATLAB/SIMULINK environment show that the proposed structure could enhance the vehicle stability and fuel economy in different manoeuvres.     

An optimal torque distribution control strategy for four-independent wheel drive electric vehicles

In this paper, an optimal torque distribution approach is proposed for electric vehicle equipped with four independent wheel motors to improve vehicle handling and stability performance. A novel objective function is formulated which works in a multifunctional way by considering the interference among different performance indices: forces and moment errors at the centre of gravity of the vehicle, actuator control efforts and tyre workload usage. To adapt different driving conditions, a weighting factors tuning scheme is designed to adjust the relative weight of each performance in the objective function. The effectiveness of the proposed optimal torque distribution is evaluated by simulations with CarSim and Matlab/Simulink. The simulation results under different driving scenarios indicate that the proposed control strategy can effectively improve the vehicle handling and stability even in slippery road conditions.     

Vehicle dynamics control of an electric-all-wheel-drive hybrid electric vehicle using tyre force optimisation and allocation

ABSTRACT

Hybrid Electric Vehicles (HEV) offer improved fuel efficiency compared to conventional vehicles at the expense of adding complexity and at times, reduced total power. As a result, HEV generally lack the dynamic performance that customers enjoy. To address this issue, the paper presents a HEV with electric All-Wheel-Drive capabilities via the use of torque vectoring electric rear axle drive (TVeRAD) to power the rear axle. The addition of TVeRAD to a front wheel drive HEV improves the total power output. To improve the handling characteristics of the vehicle, the TVeRAD provides torque vectoring at the rear axle. A bond graph model of the drivetrain is developed and used in co-simulation with CarSim. The paper proposes a control system which utilises control allocation to optimise tyre forces. The proposed control system is tested in the simulation environment with a high fidelity CarSim vehicle model. Simulation results show the control system is able to maximise vehicle longitudinal performance while avoiding tyre saturation on low mu surfaces. More importantly, the control system is able to track the desired yaw moment request on a high speed double lane change manoeuvre through the use of the TVeRAD to improve the handling characteristic of the vehicle.     

Control effects of steer-by-wire system for motorcycles on lane-keeping performance

This study discusses the control effects of the steer-by-wire (SBW) system for motorcycles on the lane-keeping performance by examining computer simulation with a rider-vehicle system which consists of a simplified vehicle model, a rider control model and the controller of the SBW system. The SBW system, which compensates the rolling angle deviation between the desired rolling angle intended by the rider and the actual rolling angle, improves the lane-keeping performance of the rider-vehicle system under the steering torque disturbance. The SBW system is, on the other hand, not effective in the lane-keeping performance under the lateral force disturbance. In addition, the lane-keeping assistance (LKA) system is applied to the SBW system and the cooperativeness of the SBW and the LKA systems is examined. The LKA system improves the lane-keeping performance of the SBW system under not only the steering torque disturbance but also the lateral force disturbance.     

A novel vehicle dynamics stability control algorithm based on the hierarchical strategy with constrain of nonlinear tyre forces

Direct yaw moment control (DYC), which differentially brakes the wheels to produce a yaw moment for the vehicle stability in a steering process, is an important part of electric stability control system. In this field, most control methods utilise the active brake pressure with a feedback controller to adjust the braked wheel. However, the method might lead to a control delay or overshoot because of the lack of a quantitative project relationship between target values from the upper stability controller to the lower pressure controller. Meanwhile, the stability controller usually ignores the implementing ability of the tyre forces, which might be restrained by the combined-slip dynamics of the tyre. Therefore, a novel control algorithm of DYC based on the hierarchical control strategy is brought forward in this paper. As for the upper controller, a correctional linear quadratic regulator, which not only contains feedback control but also contains feed forward control, is introduced to deduce the object of the stability yaw moment in order to guarantee the yaw rate and side-slip angle stability. As for the medium and lower controller, the quantitative relationship between the vehicle stability object and the target tyre forces of controlled wheels is proposed to achieve smooth control performance based on a combined-slip tyre model. The simulations with the hardware-in-the-loop platform validate that the proposed algorithm can improve the stability of the vehicle effectively.     

Vehicle velocity estimation using effective inertia for an in-wheel electric vehicle

In this study, a vehicle velocity estimation algorithm for an in-wheel electric vehicle is proposed. This algorithm estimates the vehicle velocity using the concept of effective inertia, which is based on the motor torque, the angular velocity of each wheel and vehicle acceleration. Effective inertia is a virtual mass that changes according to the state of a vehicle, such as acceleration, deceleration, turning or driving on a low friction road. The performance of the proposed vehicle velocity estimation algorithm was verified in various conditions that included straight driving, circle driving and low friction road driving using the in-wheel electric vehicle that was equipped with an in-wheel system in each of its rear wheels.     

Comparative study of vehicle tyre–road friction coefficient estimation with a novel cost-effective method

This paper qualitatively and quantitatively reviews and compares three typical tyre–road friction coefficient estimation methods, which are the slip slope method, individual tyre force estimation method and extended Kalman filter method, and then presents a new cost-effective tyre–road friction coefficient estimation method. Based on the qualitative analysis and the numerical comparisons, it is found that all of the three typical methods can successfully estimate the tyre force and friction coefficient in most of the test conditions, but the estimation performance is compromised for some of the methods during different simulation scenarios. In addition, all of these three methods need global positioning system (GPS) to measure the absolute velocity of a vehicle. To overcome the above-mentioned problem, a novel cost-effective estimation method is proposed in this paper. This method requires only the inputs of wheel angular velocity, traction/brake torque and longitudinal acceleration, which are all easy to be measured using available sensors installed in passenger vehicles. By using this method, the vehicle absolute velocity and slip ratio can be estimated by an improved nonlinear observer without using GPS, and the friction force and tyre–road friction coefficient can be obtained from the estimated vehicle velocity and slip ratio. Simulations are used to validate the effectiveness of the proposed estimation method.     

一种减轻装有EPS汽车转向扭矩的控制策略

本文提出了一种新的电动助力转向系统的控制策略,以减小车辆静止时改变方向所需的转向力。以前尝试通过减少不良的转向振动来减少转向扭矩失败的原因是因为高辅助增益往往会产生震荡或增加噪声敏感性。为了消除此种振动,开发出一种基于控制齿轮角速度的控制策略,它是在简化的转向模型的基础上开发出来的。这个实验获得了很好的齿轮角速度的估计值,这样就有可能消除方向盘所有旋转速度下的振动。实验证明在方向盘大转速变换下,转向扭矩显著降低,无振动传输给司机。所提出的控制策略使用一个辅助来获得超过原来的三倍以上的增益。此外,所提出的控制策略不需要补充传感器。     

新的轮式驱动电动车电子差速控制算法的研究

提出了一种用于轮式驱动电动车的电子差速控制算法,将转弯时转矩分配计算和基于车轮滑移率的开关控制相结合,对车辆左右驱动轮输入不同的转矩,同时根据轮胎偏转角的变化率确定目标滑移率。仿真研究证明,与采用机械差速器相比,新的电子差速控制系统鲁棒性好,车辆的驾驶更安全平稳,并能获得更优异的转向性能和更快的响应特性。     

基于模糊控制理论并联混合动力城市客车控制策略研究

简单介绍模糊控制理论及其特点,并以汽车请求转矩与发动机当前转速下转矩的差值和电池SOC值为输入、发动机期望转矩为输出设计某并联混合动力城市客车的模糊控制策略,分别采用电机辅助式控制策略和所设计的模糊控制策略进行仿真,比较两种控制策略的效果。     

基于动态门限值的分布式驱动电动汽车驱动力矩控制研究

为改善分布式驱动电动汽车高速行驶稳定性，避免频繁驱动控制操作对汽车行驶安全性的影响，提出了一种适应不同驾驶工况的参数动态门限值算法，设计了汽车附加横摆力矩滑模控制策略和驱动力矩二次规划优化分配控制策略，并进行了角阶跃输入工况和双正弦输入工况的仿真分析。结果表明，所设计的控制策略能有效控制汽车的质心侧偏角与横摆角速度，在保证汽车行驶稳定性的前提下，使质心侧偏角与理想值偏差减小了3.6%以上，轮胎附着利用率减少19.5%以上，有效地降低了轮胎附着利用率，提高了汽车的行驶安全性。     

Handling performance control for hybrid 8-wheel-drive vehicle and simulation verification

In order to improve handling performance of a hybrid 8-Wheel-Drive vehicle, the handling performance control strategy was proposed. For armoured vehicle, besides handling stability in high speed, the minimum steer radius in low speed is also a key tactical and technical index. Based on that, the proposed handling performance control strategy includes ‘Handling Stability’ and ‘Radius Minimization’ control modes. In ‘Handling Stability’ control mode, ‘Neutralsteer Radio’ is defined to adjust the steering characteristics to satisfy different demand in different speed range. In ‘Radius Minimization’ control mode, the independent motors are controlled to provide an additional yaw moment to decrease the minimum steer radius. In order to verify the strategy, a simulation platform was built including engine and continuously variable transmission systems, generator and battery systems, independent motors and controllers systems, vehicle dynamic and tyre mechanical systems. The simulation results show that the handling performance of the vehicle can be enhanced significantly, and the minimum steer radius can be decreased by 20% which is significant improvement compared to the common level of main battle armoured vehicle around the world.     

分布式驱动电动汽车转向工况转矩分配控制研究

针对分布式驱动车辆转向工况在低速下期望提高转向机动性能,高速下期望保证行驶稳定性的需求,充分考虑转向行驶内外侧车轮的转向关系以及车辆动力学,制定了适应车速变化的四轮转矩分配策略,建立了四轮轮毂电机驱动模型以及二自由度参考模型。为了改善分布式驱动转向机动性能,建立自抗扰控制器调整内外侧车轮转矩,形成合理的转速差,减小转向半径,以提高转向机动性;对于高速转向行驶稳定性的需求,通过二次规划方法优化分配各车轮驱动力矩,分析轮胎纵横向附着裕度建立目标函数,并加入附加横摆力矩和路面附着力的限制,进行车轮驱动转矩的在线优化分配,提高车辆转向行驶的稳定性;另外为避免2种控制模式转换时驱动转矩突变,根据车速和稳定性参数制定模糊规则决策2种模式的协调系数,保证2种控制模式的平滑过渡。基于CarSim和MATLAB/Simulink进行联合仿真,并搭建硬件在环平台进行试验,对所提出的方法进行验证。结果表明：在低速转向工况下,提出的分配策略能够调节内外侧车轮产生差速效果,与转矩平均分配的策略相比,转向半径有所减小,提高车辆机动性;高速转向工况下,分配策略能够保证车辆稳定转向,与未考虑稳定性控制的分配策略相比,能更好地跟踪目标轨迹,且横摆角速度控制在参考横摆角速度附近,证明了所提控制策略的有效性。     

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。     

A tyre slip-based integrated chassis control of front/rear traction distribution and four-wheel independent brake from moderate driving to limit handling

This paper presents a tyre slip-based integrated chassis control of front/rear traction distribution and four-wheel braking for enhanced performance from moderate driving to limit handling. The proposed algorithm adopted hierarchical structure: supervisor – desired motion tracking controller – optimisation-based control allocation. In the supervisor, by considering transient cornering characteristics, desired vehicle motion is calculated. In the desired motion tracking controller, in order to track desired vehicle motion, virtual control input is determined in the manner of sliding mode control. In the control allocation, virtual control input is allocated to minimise cost function. The cost function consists of two major parts. First part is a slip-based tyre friction utilisation quantification, which does not need a tyre force estimation. Second part is an allocation guideline, which guides optimally allocated inputs to predefined solution. The proposed algorithm has been investigated via simulation from moderate driving to limit handling scenario. Compared to Base and direct yaw moment control system, the proposed algorithm can effectively reduce tyre dissipation energy in the moderate driving situation. Moreover, the proposed algorithm enhances limit handling performance compared to Base and direct yaw moment control system. In addition to comparison with Base and direct yaw moment control, comparison the proposed algorithm with the control algorithm based on the known tyre force information has been conducted. The results show that the performance of the proposed algorithm is similar with that of the control algorithm with the known tyre force information.