Torque Of Traction Motor Research Articles

Robust engine slipping start control of hybrid electric vehicles with uncertainty in clutch slipping torque and change in driver demand torque

The engine slipping start (ESS) benefits parallel hybrid electric vehicles from stable ignition and emission reduction. However, inappropriate coordination between the traction motor torque and clutch slipping torque during the ESS will lead to poor smoothness of the vehicle and failed start of the engine. Uncertainty in clutch slipping torque and change in driver demand torque bring tough challenges with sluggish convergence and intensive vehicle jerk in practice. To deal with this problem, a novel two-layer model reference adaptive controller (MRAC) which contains two parallel reference models is proposed to improve robustness and convergence rate simultaneously. On one hand, uncertainties of clutch slipping torque are divided into a low-frequency part and a high-frequency part, and adaptive laws based on the output feedback are designed contrapuntally to enhance robustness. On the other hand, two parallel reference models are designed to accelerate the tracking error convergence rate without changing the reference profiles, which is generated according to the driver demand torque in real time. To test the robustness and convergence rate, the proposed two-layer MRAC is compared with the classical MRAC and proportional–integral controller under the driving scenario with uncertain clutch slipping torque and abrupt change in driver demand torque. The sensitivity with different adaptive gains and low-frequency and high-frequency uncertainties in clutch slipping torque are examined. Finally, hardware-in-the-loop experiments are performed to verify the effectiveness of the proposed two-layer MRAC.

An improved passivity‐based control for suppressing the traction motor torque ripples due to traction network voltage fluctuation in high‐speed railways

AbstractWhen the voltage fluctuation of the traction network occurs in high‐speed railways, the interharmonics in the grid‐side voltage will propagate to the traction motor, which results in the motor torque ripple of running trains. The ripple can cause abnormal vibrations of key train components and even influence train operation safety. However, the traditional proportional‐integral controller used in the inverter‐motor system has a weak anti‐interference capability when facing nonlinear disturbances. This paper proposes an improved passivity‐based control (IPBC) to suppress the impact of interharmonics on trains. First, the Euler‐Lagrange mathematical model of the traction inverter‐motor system is established. Then, the PBC for this system is designed by damping injection, ensuring the asymptotic stability of the system. Furthermore, to purposely suppress the impact of the periodic disturbance on the system, a repetitive controller is designed in parallel with the PBC to control the inverter‐motor system. Finally, through the offline simulation and HIL simulation, it has been verified that the proposed IPBC can effectively suppress the motor torque ripple and the vibrations of key train components. The control strategy proposed in this paper has a reference significance for improving the operational stability of high‐speed trains.

An adaptive receding horizon-based flexible mode switching control strategy of parallel hybrid electric vehicles

Mode switching is crucial to efficient drive in variable driving conditions for hybrid electric vehicles (HEVs), thus many scholars are attracted to implement its high-quality control. The receding horizon control method is an attractive method to solve this problem. However, the choice of prediction horizon is arduous due to the contradiction between the optimization performance and the computational cost. Motivated by this issue, this paper proposes an adaptive receding horizon control (RHC) method, which contains optimization layer (OPL) and feedback control layer (FCL). First, an OPL adaptive receding horizon control method is proposed to obtain the optimal control command, in which a novel adaptive factor, considering the proportional between the maximum traction motor torque and powertrain demand torque, is proposed to adjust the prediction horizon length and control constraints. Then, regarding OPL output as the reference trajectory, a lower-RHC method is designed in FCL to track the reference trajectory. Finally, the proposed control method is validated in simulation and bench experiment. Compared with the existing method, the clutch trajectory is optimized by RHC with adaptive prediction horizon and constrains, and the anti-disturbance ability is enhanced by the lower-RHC. The simulation and bench experiment results indicate that the 0–40 km/h acceleration time and jerk are reduced using the proposed method, respectively.

Anti-jerking and traction torque compensation strategy for P3 + hybrid electric vehicle during power upshift

In this study, an anti-jerking and traction torque compensation strategy for P3 + hybrid electric vehicle (HEV) equipped with hybrid automated mechanical transmission (HAMT) during power upshift is proposed. Firstly, to investigate the power upshift characteristics, a powertrain model with three torque ports and flexible drive shaft is established. Secondly, based on the established powertrain model, a hierarchical structure optimization strategy for power upshift is developed. The optimization strategy makes full use of the fast and accurate torque response of the traction motor, aims at simultaneously suppressing the longitudinal jerk and compensating the traction torque, solves the optimal traction motor torque to improve the power upshift performance of P3 + HEV. Finally, a layer-by-layer simulation and a real vehicle test of the power upshift process from first gear to second gear are implemented to verify the effectiveness of the proposed optimization strategy. The verification results show that the proposed strategy can realize smooth and traction torque uninterrupted power upshift process at the same time. Compared with the traditional PI controller the proposed optimization strategy can achieve smaller longitudinal jerk.

Quantitative Reliability Evaluation of Silicon Carbide-Based Inverters for Multiphase Electric Drives for Electric Vehicles

Abstract Reliability of power converter in the electric drivetrain of a vehicle can be a criterion for the comparison of various converter topologies, cooling system designs and control strategies. Therefore, reliability prediction is important for the design and control of vehicles. This paper presents an approach for quantitative evaluation of the reliability of converters for multiphase motor drives for electric vehicles (EVs) after considering the driving cycle. This paper provides a good background of reliability quantification so that it is easy to extend the presented approach to other applications. The models of subsystems have been selected to have excellent computational efficiency with good accuracy which is necessary for simulating long driving cycles. A simple vehicle model is used to obtain the traction motor torque demand for various points of the driving cycle. A multiphase interior permanent magnet synchronous motor has been used for traction motor. The operating voltage and currents of the motor are found using maximum torque per ampere (MTPA) control of IPMSM. The analytical loss calculation has been used to find the losses of switching devices of the converter. A thermal model of silicon carbide (SiC) MOSFET has been used to calculate junction temperature from the losses. The model developed here gives the failure rate and mean time between failures (MTBF) of switching devices of the inverter, which can be used to determine the failure rate. The model has been used to find the transition probabilities of a Markov model which can be used to quantify the reliability of converters of multiphase electric drives.

Basic experiments on measurement of traction coefficient between rail and wheel when traction motor torque changes

Basic experiments on measurement of traction coefficient between rail and wheel when traction motor torque changes

Study and Analysis of a Multi-Mode Power Split Hybrid Transmission

A two-motor power-split dedicated hybrid transmission (DHT) with two planetary gears is proposed for the applications of a hybrid electric vehicle (HEV) and plug-in HEV (PHEV). The proposed DHT can provide electronically controlled continuous variable transmission (eCVT) with two different gear ratios. One of two electric motors is employed to act as a speeder for splitting the input power of internal combustion engine (ICE) and the other acts as a torquer to assist ICE for boosting. Assisted by an electric motor, ICE can always be enhanced to operate at its efficient area for the benefits of fuel economy improvement. The maximum ICE torque is viable to be mechanically transmitted to vehicle wheels from standstill with two different gear ratios. This feature can help reduce the traction motor torque and power sizing significantly. The paper presents detailed theoretical analyses of the proposed eCVT. Comprehensive simulation demonstrations for a pickup truck HEV application are given to address that the vehicle fuel consumption can be considerably reduced without compromising acceleration performance.

A study on the axle load change in Electric Multiple-Unit trains caused by variation of traction motor torque

A study on the axle load change in Electric Multiple-Unit trains caused by variation of traction motor torque

Longitudinal Tire Force Estimation Using Youla Controller Output Observer

Advanced powertrain and vehicle dynamics controls often require estimates of longitudinal tire force to maximize the vehicle’s performance. One of the key advantages of hybrid electric vehicles and electric vehicles (EVs) is that measurements of the traction motor torque are readily available with good accuracy. This letter introduces a unique longitudinal tire force estimation strategy using the Youla controller output observer framework which only relies on motor torque and wheel speed measurements. The estimation strategy is applied to a rear-wheel-drive EV in order to obtain estimates of the rear axle longitudinal tire forces. A simple drivetrain model of the system is developed using bond graphs and is used in co-simulation with a high fidelity vehicle model from CarSim. It is shown in the simulation environment that the proposed estimation strategy is able to obtain accurate estimates of longitudinal tire force on high, low, and split- $\mu $ road surfaces. The proposed estimation strategy only requires information on the tire’s effective rolling radius and does not require a tire model.

Study on Active Suppression Control of Drivetrain Oscillations in an Electric Vehicle

Due to the low damping in a central driven electric vehicle and lack of passive damping mechanisms as compared with a conventional vehicle, the vehicle may endure torsional vibrations which may deteriorates the vehicle’s drivability. Thus active damping control strategy is required to reduce the undesirable oscillations in an EV. In this paper, the origin of the vibration and the design of a damping control method to suppress such oscillations to improve the drivability of an EV are studied. The traction motor torque that is given by the vehicle controller is adjusted according to the acceleration rate of the motor speed to attenuate the resonant frequency. Simulations and experiments are performed to validate the system. The results show that the proposed control system can effectively suppress oscillations and hence improve drivability.

Online Estimation of the Adhesion Coefficient and Its Derivative Based on the Cascading SMC Observer

The adhesion coefficient of wheel-rail surface cannot be directly measured, so a cascaded sliding-mode observer is proposed to observe adhesion coefficient and its derivative. A kinetic model for running heavy-duty locomotive is also established. The state equation of wheel adhesion control system is derived from the equation of traction motor torque balance, and adhesion coefficient is proposed to be calculated by load torque. Then, the cascaded sliding-mode observer is designed, and its stability is justified by Lyapunov stability. Based on the equivalence control principle for sliding-mode variable structure, an algorithm to estimate adhesion coefficient and its derivative is established. The simulation and experimental results are used to verify the effectiveness of the observer with load variations or wheel-rail status changes.

Fuzzy Logic-Based Fault Prevention of the Battery System in Hybrid Electric Vehicle

Due to high energy and power density, lithium-ion batteries (LIBs) have become one of the most popular choices for electric vehicle (EV) and hybrid electric vehicle (HEV) applications. However, reliability and durability of LIBs are highly affected by the operational and environmental conditions. The Battery Management System (BMS) is responsible for guaranteed performance and safety of batteries. Typically, the battery system protection against current or voltage fault conditions is performed using a simple on/off command from the BMS to a power contactor. However, the sudden elimination of power due to transient current or voltage changes (e.g. vehicle launch or climbing a slope) reduces the amount of energy that can be delivered and in some cases may be dangerous for the components in connection with the batteries. This paper presents the design of a closed-loop fuzzy-based control system to achieve maximum performance of the battery with regard to driving conditions such that safe operation of the battery is ensured. To do so, battery voltage or current is limited using a control input from a fuzzy controller implemented in the BMS. The vehicle Central Control Unit (CCU) corrects the traction motor torque command according to the control input received from the BMS in order to maintain battery safe operating region. This way, the battery current and voltage is limited before reaching the fault conditions, thereby improving the durability of the battery and preserving its life. Performance of the designed control system is evaluated in various driving regimes using a Hardware-in-the-Loop (HiL) test bench. Results show the efficacy of the designed control system toward the prevention of voltage and current fault conditions.

New Approach of Comprehensive Shift Schedule Based on Electric Drive Automated Mechanical Transmission

According to different control objectives, shift schedules of dynamical and economical mode for electric-drive AMT vehicles is presented and a comprehensive shift schedule model is established with precise traction motor torque and speed experimental data. The state function and objective functional are established by using dynamic programming and variety of optimal shift schedules are solved for different control weights. The simulation results indicate that the vehicle performance with comprehensive shift schedule is better than the traditional method.

Shift control of a dry-type two-speed dual-clutch transmission for an electric vehicle

In this paper, a shift control algorithm to improve the shift quality was proposed for an electric vehicle with a dry-type two-speed dual-clutch transmission. To analyse the shift characteristics of the target electric vehicle, dynamic models for the two-speed dual-clutch transmission and the drivetrain were developed. Based on the dynamic models, dynamic equations for the transient shift states were derived, and a shift performance simulator was constructed. From analysis of the transient shift state, it was found that the fluctuations in the driveshaft torque, which cause the shift quality to deteriorate, occurred as a result of the inertia torque. Based on the analytical results, a control algorithm was proposed using traction motor torque control as well as shift actuator stroke control. For traction motor control, a compensation torque was applied during the inertia phase. In that phase, actuator stroke control was performed by considering the torque margin and the kissing point during the torque phase instead of the existing map-based control. To evaluate the performance of the proposed control algorithm, a test bench for the target electric vehicle was developed. From the experimental results, it was found that the variations in the driveshaft torque and in the jerk were reduced by the proposed control algorithm, which thereby provides an improved shift quality.

Acceleration Sensorless Vibration Control of Railway Vehicle by Traction Motor Torque

This paper presents a method to suppress the vertical bending vibration of electric railcar by controlling traction motors without accelerometer. Two motors in the truck vibrate in reverse phase when truck frame vibrates vertically. Thus the truck vibration can be detected by the different rotation speed of two motors. The rotation speed of motors can be estimated by speed sensor-less control of induction motor. Experimental result using bogie testing machine with parallel cardan drive device with hollow shaft shows proportional control of differential rotation speed of two motors can decrease the truck frame vibration. However, simulation shows the proportional control of different rotation speed of two motors does not always decrease truck frame vibration depending on the truck characteristics. This paper proposes a controller by H-infinity control theory. The simulation result shows proposed controller can decrease the carbody vibration without accelerometer, even if the case of the truck characteristic is inapplicable for the proportional control.

3315 平行カルダン駆動台車における主電動機トルクによるダイナミクス制御の基礎検討(OS2-2:エレベータ・鉄道のダイナミクス,OS2:交通・物流システムのダイナミクス,オーガナイズド・セッション(OS),第18回交通・物流部門大会(TRANSLOG2009))

3315 平行カルダン駆動台車における主電動機トルクによるダイナミクス制御の基礎検討(OS2-2:エレベータ・鉄道のダイナミクス,OS2:交通・物流システムのダイナミクス,オーガナイズド・セッション(OS),第18回交通・物流部門大会(TRANSLOG2009))

Active Guidance of Railway Vehicles Using Traction Motor Torque Control

SUMMARY This paper develops the intelligent wheel concept forwarded by Wickens. A two “wheel-pair” vehicle is considered. The wheel-pair consists of two independent wheels pinned to a frame. The wheels have hub motors that provide the torque for steering as well as traction. A simple controller is applied to demonstrate the performance of the system. The maximum guidance error is shown to be 2 mm on a 54 m radius curve and the vehicle has a critical speed of 108 kph. A discussion of the merits of the system and some practical considerations are entered into.