In-wheel Brushless DC Research Articles

Modeling and control of a half electric vehicle including an inverter, an in-wheel BLDC motor and Pacejka's tire model

The problem of modeling the longitudinal motion of an Electric Vehicle (EV) or Hybrid Electric Vehicle (HEV) propelled by In-Wheel motor is considered. A complete non-linear model of the vehicle propelled by brushless DC (BLDC) in-wheel motor is presented. The model describes the association of the inverter, BLDC in-wheel motor and the chassis of the vehicle. It describes the behavior of the vehicle in the different driving phases, i.e. acceleration mode and deceleration mode. The relevant fundamental laws are used to model the chassis dynamics taking into account the different non-linear aspects such as aerodynamic effects, rolling resistance and road load. The Pacejka tire model is retained to describe the various phenomena generated at the wheel-road contact. It is shown that the proposed model describes correctly the longitudinal behavior of the vehicle in the acceleration and deceleration modes in different driving conditions.

Self-tuning fuzzy PID speed controller for quarter electric vehicle driven by In-wheel BLDC motor and Pacejka's tire model

Vehicles using internal combustion engine (ICE) adversely affect the environment. Therefore, all vehicle makers have started their mutation toward electric vehicles. In this paper, a quarter vehicle model is developed considering brushless DC (BLDC) motor actuation. The longitudinal behavior of the drive wheel is modeled using the Pacejka model or magic formula. This model describes the interaction between the tire and the road surface, which reflects road condition effect. The purpose of the control is to provide smooth speed control in both acceleration and deceleration modes, regardless of changes in road conditions. Due to the high complexity of the control model, a hybrid fuzzy-PID controller is designed to serve as a speed controller for the system motor-tire-road-surface. It is checked by numerous simulations that the proposed controller performs well, ensuring comfortable steering operation despite road characteristic changes.

Self-balancing based on Active Disturbance Rejection Controller for the Two-In-Wheeled Electric Vehicle, Experimental results

This article deals with a robust self-balancing control scheme for the Two-In-Wheeled Self-Balancing Electric-Vehicle (TIW-SB-EV). Due to time-varying and unknown torque load, uncertainties on system parameters, and the lack of knowledge of the friction components, the approach proposes the design and implementation of an active disturbance rejection control based on the extended state observer (ESO). The ESO is developed through the differentially Flatness property of the system. The system flat output measurement is obtained employing an absolute optical inclinometer, which represents the sole measurement of the plant. The electric traction for the TIW-SB-EV is composed of two In-wheel brushless DC motors (SG/F10-48 V, 800 W) powered by a controlled three-phase inverter. The TIW-SB-EV primary power source is supplied by two Lithium-Ion batteries (48 V, 10 AH). The proposed ADRC algorithm is coded on the TMS320F28335 Experimenter Kit, a device of the TMS320C28x/Delfino family. Real-time experimental results validate the mechanical design, electric drive, and control design and highlight the closed-loop robustness when the TIW-SB-EV is subjected to the endogenous and exogenous disturbances present in a real environment.

Robust Control of a Three-Phase Synchronous In-wheel Motor

This paper discusses a robust torque and speed control strategy for an In-wheel Brushless DC Synchronous Machine (IWBLDC). In addition, we introduce a novel processing pipeline to increase the precision of angle measurement from a reduced set of square-wave Hall sensors. The disturbances in the electrical subsystem, including the trapezoidal back-electromotive force, are estimated with a disturbance observer. We add a correction term to ensure the rejection of variations of parameters and cancel coupling effects between the stator axis. The algorithm is executed on the digital signal processor TMS320f28379d and validated on a test bench equipped with a 500W nominal power IWBLDC.

DETECCIÓN MULTICRITERIO DE FALLOS DE UN MOTOR BLDC (BRUSHLESS DIRECT CURRENT)

This work presents a multiple criteria approach for stator fault detection (FD) in an in-wheel brushless DC (BLDC) motor for electric vehicles. The detection of inter-turn short circuits in the stator windings of the BLDC is studied. The fault detection scheme is performed based on the instantaneous space phasor (ISP). The fault signature (residual) is built using the fast Fourier transform (FFT) and discrete wavelet transform (DWT). An experimental setup comprising a modified in-wheel BLDC was used to validate this approach. The results of signal processing based FD are verified by an analysis made with thermographic techniques. Key Words: in-wheel BLDC motor, fault detection, FFT, DWT, entropy, infrared image, electric vehicle.

Determination of the road load on electric two-wheelers using the torque-current relationship of the drive motor

We propose a new drive performance test method to measure the road load of e-bikes driven by in-wheel brushless DC (BLDC) motors during a road drive. This method is quite different from the commonly used coastdown test. In our proposed method, speed and road load were correlated by fitting the speed and current consumption of the motor when driving at constant speed on a uniform horizontal road. The method was tested by riding an e-bike on a real road. The torque and the current with torque constant of the in-wheel motor of the e-bike were linearly related. We also conducted a coastdown test on the same road. By comparing the experimental results of the two field tests, the applicability of our new method was verified. Based on these results, we conclude that the proposed method can be used to measure the road load of the e-bike, including its rolling and aerodynamic resistances, satisfactorily.

An Improved DTC for In-wheel BLDC motors in Micro All-electric Vehicles

The micro all-electric vehicle pertaining to this study is rear-driven, with motors in the left and right rear wheels. The motors are brushless dc (BLDC) using Hall effect sensors with a trapezoidal back-electromotive force. The control system is developed by using a digital signal processor. To thoroughly utilize the fast torque generation feature of BLDC motors, direct torque control (DTC) is preferable, but with conventional DTC, dead-time must be added. This paper proposes an improved DTC, where the switching device operating principle is equivalent to that of a unipolar pulse width modulation (PWM) technique named PWM-ON. Dead-time is not required, and switching losses are reduced. Further analysis showed that under the improved DTC the dc supply took up only the load current, confirming that there was no return of load energy to the dc supply, which protects the batteries. Experimental results are given to confirm validity.

1인승 전기차량의 임베디드 전동제어장치 설계

본 논문은 1인승 전기차량의 임베디드 전동 제어장치 설계를 제안하였다. 제안된 임베디드 장치는 PIC18F8720 프로세서, 16Mb flash ROM, 32Mb SDRAM과 신호처리회로로 설계되었다. 제안된 1인승 전기차량은 4KW 인휠 BLDCM, <TEX>$180^{\circ}$</TEX> 도통 공간 벡터제어 3상 전압형 인버터, PID 속도제어기와 전동제어 장치와 임베디드 제어장치로 구성된다. 이 1인승 전기차량은 역 3륜 형태의 기계적인 구조를 가지고 있으며, 인휠 BLDCM과 틸팅 기능을 가지는 조향 메카니즘이 적용되었다. 또한 제안된 임베디드 전동제어장치의 성능은 PEV에 대한 Lab 실험과 도로 주행시험을 통하여 검증하였다. This paper presents the design of embedded electrical power control unit for Personal Electrical Vehicle(PEV). The embedded unit is designed using PIC18F8720 processor, 16Mb flash ROM, 32Mb SDRAM and signal condition circuits. The proposed PEV consists of 4KW in-wheel Brushless DC Motor(BLDCM), 3 phase voltage source inverter with the <TEX>$180^{\circ}$</TEX> conduction space vector PWM method, PID speed controller and the embedded control unit. The PEV has mechanical manufacture of inverse 3 wheel system, which is applied by the in-wheel BLDCM and steering mechanism with tilting function. Also, the performances of the proposed embedded electrical power control unit are verified through the lab experiment and road driving test of PEV.