Integrated Active Suspension and Anti-Lock Braking Control for Four-Wheel-Independent-Drive Electric Vehicles

This paper presents an integrated control scheme for enhancing the ride comfort and handling performance of a four-wheel-independent-drive electric vehicle through the coordination of active suspension system(ASS)and anti-lock braking system(ABS).First,a longitudinal-vertical coupled vehicle dynamics model is established by integrating a road input model.Then the coupling mechanisms between longitudinal and vertical vehicle dynamics are analyzed.An ASS-ABS integrated control system is proposed,utilizing an H∞controller for ASS to optimize load transfer effect and a neural network sliding mode control for ABS implementation.Finally,the effectiveness of the proposed control scheme is evaluated through comprehensive tests conducted on a hardware-in-loop(HIL)test platform.The HIL test results demonstrate that the proposed control scheme can significantly improve the braking performance and ride comfort compared to conventional ABS control methods.

Investigating the Impact of Base Heating and External Electric Field on PV Cell Performance under Intense Illumination

The characterization of the performances of a PV cell is linked to intrinsic factors of this cell. It is therefore important for us to identify the favorable or unfavorable conditions that affect the performance of PV cells. It is from this perspective that it seems judicious to us to study the simultaneous influence of the heating of the base and an external electric field on the performance of a PV cell under intense illumination of 50 suns. Two phenomena contribute to the heating of the base of a PV cell which is heating due to the transfer by conduction of solar radiation energy received by the surface of the PV cell and the heat generated inside the PV cell by various phenomena linked to the movement of photogenerated charged carriers. In this study, we take into account the heating linked to the movement of the charged carriers in the base. After a mathematical modeling of the PV cell considered, some hypotheses are formulated and the expressions of the electrical parameters are established as a function of the electric field and base temperature. Subsequently, we use numerical simulation to highlight the behavior of theses parameters as a function of temperature and of the intensity of the electric field. The results show that for any given temperature, the orientation of the electric field as considered in our work improves the performance of the PV cell while high temperatures degrade these performances. Furthermore, the analysis of the curves shows that the harmful effect of temperature on the performance of a PV cell is more accentuated at large values of electric field.

Design and Analysis of Electro-mechanical Hybrid Anti-lock Braking System for Hybrid Electric Vehicle Utilizing Motor Regenerative Braking

Braking on low adhesion-coefficient roads, hybrid electric vehicle＇s motor regenerative torque is switched off to safeguard the normal anti-lock braking system （ABS） fimction. When the ABS control is terminated, the motor regenerative braking is readmitted. Aiming at avoiding permanent cycles from hydraulic anti-lock braking to motor regenerative braking, a novel electro-mechanical hybrid anti-lock braking system using fuzzy logic is designed. Different from the traditional single control structure, this system has a two-layered hierarchical structure, The first layer is responsible for harmonious adjustment or interaction between regenerative system and anti-lock braking system. The second layer is responsible for braking torque distribution and adjustment. The closed-loop simulation model is built. Control strategy and method for coordination between regenerative and anti-lock braking are developed. Simulation braking on low adhesion-coefficient roads with fuzzy logic control and real vehicle braking field test are presented. The results from simulating analysis and experiment show braking performance of the vehicle is perfect, harmonious coordination between regenerative and anti-lock braking function, significant amount of braking energy can be recovered and the proposed control strategy and method are effective.

Driving and Braking Control of PM Synchronous Motor Based on Low-resolution Hall Sensor for Battery Electric Vehicle

Resolvers are normally employed for rotor positioning in motors for electric vehicles, but resolvers are expensive and vulnerable to vibrations. Hall sensors have the advantages of low cost and high reliability, but the positioning accuracy is low. Motors with Hall sensors are typically controlled by six-step commutation algorithm, which brings high torque ripple. This paper studies the high-performance driving and braking control of the in-wheel permanent magnetic synchronous motor （PMSM） based on low-resolution Hall sensors. Field oriented control （FOC） based on Hall-effect sensors is developed to reduce the torque ripple. The positioning accuracy of the Hall sensors is improved by interpolation between two consecutive Hall signals using the estimated motor speed. The position error from the misalignment of the Hall sensors is compensated by the precise calibration of Hall transition timing. The braking control algorithms based on six-step commutation and FOC are studied. Two variants of the six-step commutation braking control, namely, half-bridge commutation and full-bridge commutation, are discussed and compared, which shows that the full-bridge commutation could better explore the potential of the back electro-motive forces （EMF）, thus can deliver higher efficiency and smaller current ripple. The FOC braking is analyzed with the phasor diagrams. At a given motor speed, the motor turns from the regenerative braking mode into the plug braking mode if the braking torque exceeds a certain limit, which is proportional to the motor speed. Tests in the dynamometer show that a smooth control could be realized by FOC driving control and the highest efficiency and the smallest current ripple could be achieved by FOC braking control, compared to six-step commutation braking control. Therefore, FOC braking is selected as the braking control algorithm for electric vehicles. The proposed research ensures a good motor control performance while maintaining low cost and high reliability.

Aircraft Electric Anti-skid Braking System Based on Fuzzy-PID Controller with Parameter Self-adjustment Feature

The principle of electric braking system is analyzed and an anti-skid braking system based on the slip rate control is proposed.The fuzzy-PID controller with parameter self-adjustment feature is designed for the anti-skid braking system.The dynamic model of aircraft ground braking is established in the simulation environment of MATLAB/SIMULINK,and simulation results of dry runway and wet runway are presented.The results show that the fuzzy-PID controller with parameter self-adjustment feature for the electric anti-skid braking system keeps working in the state of stability and the brake efficiencies are increased to 93%on dry runway and 82%on wet runway respectively.

Energy-Optimal Braking Control Using a Double-Layer Scheme for Trajectory Planning and Tracking of Connected Electric Vehicles

Most researches focus on the regenerative braking system design in vehicle components control and braking torque distribution,few combine the connected vehicle technologies into braking velocity planning.If the braking intention is accessed by the vehicle-to-everything communication,the electric vehicles(EVs)could plan the braking velocity for recovering more vehicle kinetic energy.Therefore,this paper presents an energy-optimal braking strategy(EOBS)to improve the energy efficiency of EVs with the consideration of shared braking intention.First,a double-layer control scheme is formulated.In the upper-layer,an energy-optimal braking problem with accessed braking intention is formulated and solved by the distance-based dynamic programming algorithm,which could derive the energy-optimal braking trajectory.In the lower-layer,the nonlinear time-varying vehicle longitudinal dynamics is transformed to the linear time-varying system,then an efficient model predictive controller is designed and solved by quadratic programming algorithm to track the original energy-optimal braking trajectory while ensuring braking comfort and safety.Several simulations are conducted by jointing MATLAB and CarSim,the results demonstrated the proposed EOBS achieves prominent regeneration energy improvement than the regular constant deceleration braking strategy.Finally,the energy-optimal braking mechanism of EVs is investigated based on the analysis of braking deceleration,battery charging power,and motor efficiency,which could be a guide to real-time control.

A new braking force distribution strategy for electric vehicle based on regenerative braking strength continuity

Regenerative braking was the process of converting the kinetic energy and potential energy, which were stored in the vehicle body when vehicle braked or went downhill, into electrical energy and storing it into battery. The problem on how to distribute braking forces of front wheel and rear wheel for electric vehicles with four-wheel drive was more complex than that for electric vehicles with front-wheel drive or rear-wheel drive. In this work, the frictional braking forces distribution curve of front wheel and rear wheel is determined by optimizing the braking force distribution curve of hydraulic proportional-adjustable valve, and then the safety brake range is obtained correspondingly. A new braking force distribution strategy based on regenerative braking strength continuity is proposed to solve the braking force distribution problem for electric vehicles with four-wheel drive. Highway fuel economy test(HWFET) driving condition is used to provide the speed signals, the braking force equations of front wheel and rear wheel are expressed with linear equations. The feasibility, effectiveness, and practicality of the new braking force distribution strategy based on regenerative braking strength continuity are verified by regenerative braking strength simulation curve and braking force distribution simulation curves of front wheel and rear wheel. The proposed strategy is simple in structure, easy to be implemented and worthy being spread.

Regenerative braking control for hybrid electric vehicles under decelerating condition

The operating mode of a single shaft hybrid electric vehicle （SSHEV） in which the electric motor exerts negative torque on the shaft to imitate engine braking is analyzed. The method of determining the quantity of regenerative braking torque is proposed with the premise that the braking intensity required by the driver is satisfied. On this basis, factors that affect torque generated by the motor are listed, and how the battery＇ s temperature and state of charge （ SOC ） restrict and correct the braking torque is expounded. Finally, road test results show that the motor＇ s constant power or constant torque control is an effective way to recover the mechanical energy during decelerating.

An Investigation into Regenerative Braking Control Strategy for Hybrid Electric Vehicle

Energy regeneration during braking is an important technique for hybrid electric vehicle (HEV) to improve their fuel economy and extend their driving range. Due to the effect of regenerative braking torque which is added by electric motor, the braking torque distribution between front and rear axles should be changed and the control logic of anti-lock braking system (ABS) ought to be adjusted according to the regenerative braking torque. This paper put forward a braking control strategy for hybrid electric vehicle; the control strategy is implemented with eight DOFs (Degree-of-Freedom) nonlinear vehicle forward simulation model which is built under the environment of Matlab/Simulink. Based on target wheel slip ratio, a fuzzy logic approach was applied to maintain the optimal target slip ratio so that best compromise between hydraulic torque and regenerative torque can be obtained for the vehicle.

Wide speed range for traction motor in braking force of electric braking control system

A vehicle stopping method using an electric brake until a traction motor is stopped is studied. At the moment of vehicle stop, electric brake is changed to control mode where torque is reduced at a low speed. Gradient is controlled by estimating the load torque of motor, thereby traction motor is not rotated after stop. In addition, coasting operation and brake test are performed from normal-opposite operation and start using a small-scale model comprising the inertial load equipment and the power converter. Further, traction motor is made to be equipped with a suspension torque. Pure electric braking that makes traction motor stop by an air brake at the time of stop is also implemented. Constant torque range and constant power range are expanded during braking so that braking force is secured with the electric brakes even in high speed region. Therefore, vehicle reduction effect can be expected by reducing parts related with an air brake which is not used frequently by using a pure electric brake in the M car in wide speed region. Further, maintenance of brake system can be reduced. Besides, ride comfort of passenger in the electric rail car, energy efficiency improvement, and noise reduction effect can be additionally expected. Further, an improved brake method that uses only an electric brake till motor stop is proposed by comparing those in the blending brake that uses an air brake while reducing brake torque at vehicle stop.

Electro-mechanical Braking Method in Hybrid Electric Vehicles Based on Feedback Control Theory

In this paper, the hybrid electric vehicle braking process is researched, by using variables consists of HEV speed, motor speed, and state of charge established, fimctions of mechanical braking force, regenerative braking force and efficiency of energy recovery are constructed, and the control goal is to maximization the energy recovery efficiency. Under the feedback control strategy, with the constrain condition of braking strength and braking stability, combining experiments in ADVISOR, in different experiments of different working conditions, we can see that in UDDS Cycle, the regenerative braking efficiency is the best. What＇s more, compared with strategies in ADVISOR, strategy proposed in this paper is obviously better.

A Novel Braking Control Strategy for Hybrid Electric Buses Based on Vehicle Mass and Road Slope Estimation

Proper braking force distribution strategies can improve both stability and economy performance of hybrid electric vehicles,which is prominently proved by many studies.To achieve better dynamic stable performance and higher energy recovery efficiency,an effective braking control strategy for hybrid electric buses(HEB)based on vehicle mass and road slope estimation is proposed in this paper.Firstly,the road slope and the vehicle mass are estimated by a hybrid algorithm of extended Kalman filter(EKF)and recursive least square(RLS).Secondly,the total braking torque of HEB is calculated by the sliding mode controller(SMC),which uses the information of brake intensity,whole vehicle mass,and road slope.Finally,comprehensively considering driver’s braking intention and regulations of the Economic Commission for Europe(ECE),the optimal proportional relationship between regenerative braking and pneumatic braking is obtained.Furthermore,related simulations and experiments are carried out on the hardware-in-the-loop test bench.Results show that the proposed strategy can effectively improve the braking performance and increase the recovered energy through precise control of the braking torque.

Identification and Modeling of Automotive Electrical Parking Brake System for SiL Simulation

To evaluate the software behavior of the electronic control unit （ECU） of automotive electrical parking brake （EPB）, a software- in-the-loop （SiL） simulation system is built. The EPB is simulated by ARX （auto-regressive with auxiliary input） model, ARMAX （auto-regressive moving average with auxiliary input） model, and NNARMAX （neural network ARMAX） model. By system identification, the ARX（3,4,2）, ARX（4,4,2）, ARMAX（3,3,1,1）, and ARMAX（4,4,3,2） models are derived. Validation results show that the four-order ARMAX model and the NNARMAX model better simulate the actuator of the EPB.

Research on the Control Method of Electromechanical Composite Brake Based on Electric Wheel Drive Vehicle

Facing the increasingly serious environmental pollution and oil crisis,the development of automobile industry is facing a very serious challenge.For the sustainable development of automobile industry,the electric vehicle using motor as driving equipment can realize“pollution-free”,which has become the focus of automobile research and development in many countries.In the research and development of electric vehicles,the electric vehicles driven by electric wheels have attracted the attention of all walks of life because of their ideal control characteristics and broad application prospects.In this paper,the electric wheel drive vehicle as the research object,the electromechanical composite brake control system is studied and analyzed.

The Summary of the Research on the Compound Braking Strategy of Four Wheel Hub Motor Drive Electric Vehicle

This paper describes in detail three kinds of typical compound braking strategy of wheel motor drive electric vehicle and summarizes the current commonly used strategies based on the three typical strategies developed. In the end, a new compound braking strategy is proposed;that is, we take braking mode classify, ECE regulations and SOC value of the battery as an important reference of braking force that joins the motor braking force, as well as we join the different identification models;according to the different braking modes, the purpose is that we can apply the different braking program.

A novel predictive braking energy recovery strategy for electric vehicles considering motor thermal protection

Braking energy recovery(BER)aims to recover the vehicle's kinetic energy by coordinating the motor and mechanical braking torque to extend the driving range of the electric vehicle(EV).To achieve this goal,the motor/generator mode requires frequent switching and prolonged operation during driving.In this case,the motor temperature will unavoidably rise,potentially triggering motor thermal protection(MTP).Activating MTP increases the risk of motor component failure,and the EV typically disables the BER function.Thus,maximizing BER while reducing the risk of motor overheating is a challenging problem.To address this issue,this article proposes a predictive BER strategy with MTP using the non-smooth Pontryagin Minimum Principle(NSPMP)for EVs.Firstly,a Markov long short-term memory(MLSTM)model is designed to obtain future velocity information.Secondly,the BER problem with MTP in the studied EV is embedded in a model predictive control(MPC)framework.Then,under the MPC framework,the NSPMP strategy is proposed to resolve the problem of MTP.Finally,the performance of the proposed strategy is verified through simulation and a hardware-in-loop test.The results show that in two real-world driving cycles,compared to the rule-based strategy,the proposed strategy reduced power consumption by 1.24%and0.96%,respectively,and effectively limited motor temperature.Additionally,under global cycle conditions,this strategy demonstrated better MTP control performance compared to other benchmark strategies.

Longitudinal train dynamics of electric multiple units under rescue

Once operating trains are disabled on the railway lines,an efficient manner is to utilize the train for train rescue.Owning to the different train and coupler types,it is difficult to formulate uniform regulations for train to train rescue.In this paper,the longitudinal train dynamics of electric multiple units under rescue were analyzed by field and laboratory tests.The angling behavior of the brakinginduced coupler under compressed in-train forces was analyzed.A dynamic model for the train and draft gear system was developed considering accurate boundary limitations and braking characteristics.The safety indices and their limits for the coupled rescue train were defined.Thedynamic evaluations of different train to train rescue scenarios were analyzed.It is indicated that the coupler vertical rotation occurs during the emergency braking applied by the assisting train.The vertical force components of intrain forces lead to the carbody pitch behavior and even cause local destructions to the coupler system.The carbody pitch motion can arise the inference of in-train devices.Based on the safety evaluation of train and coupler system,the regulations for typical train to train rescue scenarios were formulated.

Control Algorithm of Electric Vehicle in Coasting Mode Based on Driving Feeling

Coasting in gear is a common driving mode for the conventional vehicle equipped with the internal combustion engine（ICE）, and the assistant braking function of ICE is utilized to decelerate the vehicle in this mode. However, the electric vehicle（EV） does not have this feature in the coasting mode due to the relatively small inertia of the driving motor, so it will cause the driver cannot obtain the similar driving feeling to that of the conventional vehicle, and even a traffic accident may occur if the driver cannot immediately adapt to the changes. In this paper, the coasting control for EV is researched based on the driving feeling. A conventional vehicle equipped with continuously variable transmission（CVT） is taken as the reference vehicle, and the combined simulation model of EV is established based on AVL CRUISE and MATLAB/Simulink. The torque characteristic of the CVT output shaft is measured in coasting mode, and the data are smoothed and fitted to a polynomial curve. For the EV in coasting mode, if the state of charge（SOC） of the battery is below 95%, the polynomial curve is used as the control target for the torque characteristic of the driving motor, otherwise, the required torque is replaced by hydraulic braking torque to keep the same deceleration. The co-simulation of Matlab/Simulink/Stateflow and AVL CRUISE, as well as the hardware-in-loop experiment combined with d SPACE are carried out to verify the effectiveness and the real-time performance of the control algorithm. The results show that the EV with coasting braking control system has similar driving feeling to that of the reference vehicle, meanwhile, the battery SOC can be increased by 0.036% and 0.021% in the initial speed of 100 km/h and 50 km/h, respectively. The proposed control algorithm for EV is beneficial to improve the driving feeling in coasting mode, and it also makes the EV has the assistant braking function.

Slip-Control Strategy of Dual Independent Electric Drive Tracked Vehicle

In order to improve the brake performance of a dual independent electric drive tracked vehicle,a dynamic model for braking situation was established.Then,a sliding model controller(SMC)with an auxiliary system was designed to control the slip and its effectiveness was proved.A hardware-in-loop simulation through MATLAB/XPC was compared with the normal SMC and normal integral sliding mode controller(ISMC),the results show that SMC with the auxiliary system has a better performance:a smaller overshoot and steady state error.The disturbance is suppressed effectively.In the initial speed of 65.km/h,the brake distance was shortened by 3.4%and 6.8%compared with the other two methods,respectively.Finally,initial speeds of 30-36.km/h tests was carried out on a flat soil road.Compared with a no-control brake,the displacement was shortened by 1.8.m.It demonstrates the effectiveness of the slip-control strategy.In the same situation,the error between the simulation and test is 18.1%,which validates the accuracy of models.

考虑道路识别的四驱电动汽车再生制动策略

为了充分利用路面附着条件分配再生制动力,提高制动能量回收率,根据双电动机四驱结构电动汽车复合制动系统的特点,对其制动能量回收控制策略进行了研究.分析了驱动轮与地面附着特性,设计了道路识别器来计算每个轮胎与当前路面之间的峰值附着系数,并使用模糊控制策略确定每个车轮与8种道路的滑移率和附着利用率的相似输入.根据双电动机外部特性的制动力分配关系,提出了使更多制动能量回馈给电池的策略.结果表明:制动强度为0.3时,能量回收率为65.55%,具有较高的回收效率.