Dongbin Lu

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.

Torque-based optimal acceleration control for electric vehicle

The existing research of the acceleration control mainly focuses on an optimization of the velocity trajectory with respect to a criterion formulation that weights acceleration time and fuel consumption. The minimum-fuel acceleration problem in conventional vehicle has been solved by Pontryagin’s maximum principle and dynamic programming algorithm, respectively. The acceleration control with minimum energy consumption for battery electric vehicle(EV) has not been reported. In this paper, the permanent magnet synchronous motor(PMSM) is controlled by the field oriented control(FOC) method and the electric drive system for the EV(including the PMSM, the inverter and the battery) is modeled to favor over a detailed consumption map. The analytical algorithm is proposed to analyze the optimal acceleration control and the optimal torque versus speed curve in the acceleration process is obtained. Considering the acceleration time, a penalty function is introduced to realize a fast vehicle speed tracking. The optimal acceleration control is also addressed with dynamic programming(DP). This method can solve the optimal acceleration problem with precise time constraint, but it consumes a large amount of computation time. The EV used in simulation and experiment is a four-wheel hub motor drive electric vehicle. The simulation and experimental results show that the required battery energy has little difference between the acceleration control solved by analytical algorithm and that solved by DP, and is greatly reduced comparing with the constant pedal opening acceleration. The proposed analytical and DP algorithms can minimize the energy consumption in EV’s acceleration process and the analytical algorithm is easy to be implemented in real-time control.

Instantaneous optimal regenerative braking control for a permanent-magnet synchronous motor in a four-wheel-drive electric vehicle

Recovering the kinetic energy of a vehicle is one inherent advantage of an electric vehicle. A permanent-magnet synchronous motor is widely adopted for the traction motor in an electric vehicle with the advantage of a high efficiency and a high torque density. The principle for electric braking control of the permanent-magnet synchronous motor under field-oriented control is studied. The efficiency model of the electric drive system, which is different from that of the internal-combustion engine drive system, can be exactly described by analytical equations. On this basis, the battery power can be expressed as a function of the angular velocity and the electromagnetic torque of the motor. By solving the partial differential equation for the battery power, the instantaneous optimal regenerative braking torque of the permanent-magnet synchronous motor is simply calculated according to the vehicle braking torque demand and the motor speed. Compared with the existing efficiency map method, the analytical technology is easily implemented. Then a four-wheel-drive electric vehicle is investigated to achieve optimal regenerative braking control. The dynamic behaviour of braking in the four-wheel-drive electric vehicle is also considered. The parallel braking pattern and the series braking pattern are investigated in order to evaluate the availability of braking energy recovery. The instantaneous optimal regeneration energy can be recovered for the series braking system, and a significant amount of energy can be recovered for the parallel braking system by adjusting the free travel of the brake pedal.

Rule-based fault diagnosis of hall sensors and fault-tolerant control of PMSM

Hall sensor is widely used for estimating rotor phase of permanent magnet synchronous motor(PMSM). And rotor position is an essential parameter of PMSM control algorithm, hence it is very dangerous if Hall senor faults occur. But there is scarcely any research focusing on fault diagnosis and fault-tolerant control of Hall sensor used in PMSM. From this standpoint, the Hall sensor faults which may occur during the PMSM operating are theoretically analyzed. According to the analysis results, the fault diagnosis algorithm of Hall sensor, which is based on three rules, is proposed to classify the fault phenomena accurately. The rotor phase estimation algorithms, based on one or two Hall sensor(s), are initialized to engender the fault-tolerant control algorithm. The fault diagnosis algorithm can detect 60 Hall fault phenomena in total as well as all detections can be fulfilled in 1/138 rotor rotation period. The fault-tolerant control algorithm can achieve a smooth torque production which means the same control effect as normal control mode (with three Hall sensors). Finally, the PMSM bench test verifies the accuracy and rapidity of fault diagnosis and fault-tolerant control strategies. The fault diagnosis algorithm can detect all Hall sensor faults promptly and fault-tolerant control algorithm allows the PMSM to face failure conditions of one or two Hall sensor(s). In addition, the transitions between health-control and fault-tolerant control conditions are smooth without any additional noise and harshness. Proposed algorithms can deal with the Hall sensor faults of PMSM in real applications, and can be provided to realize the fault diagnosis and fault-tolerant control of PMSM.

Research on hub motor control of four-wheel drive electric vehicle

The Four-wheel drive electric vehicle (EV) is driven by four hub motors. In the hub motor drive system, three hall-effect sensors are usually used to provide absolute rotor position information, correspond to the block commutation algorithm for BLDC motors. However, the waveform of the back electromotive force (EMF) of the hub motor is not trapezoidal, but between sinusoidal and trapezoidal shape. The amplitude of the torque ripple at low speed is large and the frequency is close to resonant frequency. As a result, when the EV drives at low speed, the noise is serious. A sinusoidal current drive system of sinusoidal-wave PM motor with a low resolution position sensor is proposed in paper [1]. At low speed, the performance of the sinusoidal current control is perfect, and the torque ripple is much lower than that of the block commutation algorithm. However, the noise increases at middle and high speed because of the switching noise and harmonics. This paper proposes a combined BLDC and PMSM control for the hub motors. Sinusoidal control or field oriented control is applied for the hub motor at low speed, while block commutation algorithm is used at middle and high speed. A low noise level of the driving cab in all speed range can be reached. The electric braking method for the Four-wheel drive EV is also introduced. The proposed methodology is demonstrated by vehicle test, and is shown to achieve low noise level and dynamic performance.

Optimal Velocity Control for a Battery Electric Vehicle Driven by Permanent Magnet Synchronous Motors

The permanent magnet synchronous motor (PMSM) has high efficiency and high torque density. Field oriented control (FOC) is usually used in the motor to achieve maximum efficiency control. In the electric vehicle (EV) application, the PMSM efficiency model, combined with the EV and road load system model, is used to study the optimal energy-saving control strategy, which is significant for the economic operation of EVs. With the help of GPS, IMU, and other information technologies, the road conditions can be measured in advance. Based on this information, the optimal velocity of the EV driven by PMSM can be obtained through the analytical algorithm according to the efficiency model of PMSM and the vehicle dynamic model in simple road conditions. In complex road conditions, considering the dynamic characteristics, the economic operating velocity trajectory of the EV can be obtained through the dynamic programming (DP) algorithm. Simulation and experimental results show that the minimum energy consumption and global energy optimization can be achieved when the EV operates in the economic operation area.

High-performance control of PMSM based on a new forecast algorithm with only low-resolution position sensor

The high performance drives of the permanent magnet synchronous motor can be achieved by vector control. In such high performance drive system, a high resolution position sensor is desired. In this paper, a new forecast algorithm is proposed to predict the position and speed of the rotor with only a low accuracy sensor, which is used instead of a conventional high-resolution position sensor. The new algorithm estimates the rotor position by detecting the rotor speed and acceleration in the previous interrupted cycle of position signal. Simulation and experimental results show that the algorithm can estimate the rotor position successfully and realize the vector control. The system is shown to remain stable and accurate while the motor is uniform, speed up and slow down.

Design of the control system for a four-wheel driven micro electric vehicle

In this paper, the control system for a four-wheel-driven micro electric vehicle has been designed, which consists of vehicle control unit (VCU), wheel-motor control unit (MCU), battery management system (BMS) and time-triggered CAN (TTCAN) communication network. The VCU, as a key component of the whole system, gives orders to other modules based on the driver manipulation, data from other modules via TTCAN and information collected by other vehicle sensors. The battery management system (BMS) is responsible for the battery maintenance and state estimation. The four motor control units (MCU) control the wheel motor locally according to the command from VCU. The TTCAN network is based on the conventional CAN and realized by software.

Economic operating characteristics of permanent magnet synchronous motor in electric vehicle

Permanent magnet synchronous motor (PMSM) is of high efficiency and high torque density. The field oriented control (FOC) is usually used in the motor and the maximum efficiency control can be achieved. In electric vehicle (EV) application, the PMSM efficiency model, combining with the EV and road load system, is used to study the optimal energy-saving control strategy, which is significant for the economic operation of EV. With the help of GPS,IMU and other information technology, the road conditions can be measured. For simple road conditions, the economic operating points of PMSM can be obtained through the efficiency model of PMSM and the vehicle dynamic model of EV. For complex road conditions, considering the dynamic characteristics, the economic operating trajectory of PMSM can be obtained through dynamic programming (DP) algorithm. Simulation and experiment results show that the optimum mileage and global energy optimization can be achieved when the PMSM operates in the economic operation area.

Field Oriented Control of Permanent Magnet Brushless Hub Motor in Four-Wheel Drive Electric Vehicle

The back electromotive force (EMF) waveform of permanent magnet (PM) brushless hub motor is usually nearly sinusoidal, which is suitable for sinusoidal current control. The field oriented control based on hall-effect sensors is applied to minimize the torque ripple in this paper. The estimated rotor position through the interpolation method is calculated by the signals of the hall-effect sensors. A feed forward controller is developed to eliminate the instantaneous great torque change of the motor to reduce the torque ripple. The results show that the field oriented control with feed forward control eliminates the vehicle irregularity.