A Sensolrless Speed Control System for an Electric Vehicle without Mechanical Differential Gear

Cordeiro, Armando; Foito, Daniel; Guerreiro, M.

doi:10.1109/melcon.2006.1653310

Cited by 17 publications

(9 citation statements)

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“…This figure clearly shows that the estimated speed during this test correctly follows the measured one even at zero-speed. This was not the case in [31], where the estimation failed around zero-speed especially at no-load. Fig.…”

Section: A Rnn Control Strategy Testsmentioning

confidence: 85%

Modeling, Analysis, and Neural Network Control of an EV Electrical Differential

Haddoun

Benbouzid

Diallo

et al. 2008

IEEE Trans. Ind. Electron.

115

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Abstract-This paper presents system modeling, analysis, and simulation of an electric vehicle (EV) with two independent rear wheel drives. The traction control system is designed to guarantee the EV dynamics and stability when there are no differential gears. Using two in-wheel electric motors makes it possible to have torque and speed control in each wheel. This control level improves EV stability and safety. The proposed traction control system uses the vehicle speed, which is different from wheel speed characterized by a slip in the driving mode, as an input. In this case, a generalized neural network algorithm is proposed to estimate the vehicle speed. The analysis and simulations lead to the conclusion that the proposed system is feasible. Simulation results on a test vehicle propelled by two 37-kW induction motors showed that the proposed control approach operates satisfactorily.

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Section: A Rnn Control Strategy Testsmentioning

confidence: 85%

Modeling, Analysis, and Neural Network Control of an EV Electrical Differential

Haddoun

Benbouzid

Diallo

et al. 2008

IEEE Trans. Ind. Electron.

115

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“…Then the estimate ω of the motor speed ω equals E/K b . This method is convenient to apply in microcontrollerbased control of a PMDC motor driven by switch-mode dc-dc converters; see [6], [7], [8], [9]. While this method does not suffer from the drawbacks of the above-discussed methods, there may be significant errors between ω and the desired speed ω d , as in [8], and as seen in the present paper.…”

Section: Introductionmentioning

confidence: 88%

Sensorless speed control of a permanent magnet DC motor by compensating the plant nonlinearities

Saurav

Potluri

2013

2013 IEEE International Symposium on Industrial Electronics

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Permanent magnet dc motors are popular for the simplicity of their control. Exist a few methods of sensorless speed control (SSC) of these motors. Each of these methods has its limitations that restrict its wider applicability. One of these methods uses the sensing of applied armature voltage and armature current to obtain an estimate of the motor speed, and then uses this estimate for the feedback control of the motor speed. In the microcontroller-based control of a PMDC motor, or a dc motor with separate fixed excitation, driven by a switchmode dc-dc converter, the converter may have a nonlinear inputoutput characteristic that reduces the tracking accuracy of this method. This paper presents a way to obtain a compensator of this characteristic automatically, and to thus improve the performance of the method.

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“…The suspension system is neglected for the sake of simplicity. The equations can be expressed as follows [4,5] …”

Section: A Dynamicfunction Ofthe Evmentioning

confidence: 99%

“…speeds and the driver demand from the two motors and the driver, respectively. All gating signals for power switches are determined at every sample instant by a single microcontroller, which collects and analyzes the data from the accelerator pedal, the steering angle, the voltage and current from each motor to perform the necessary speed estimation and control [4]. After calculating the required demand according to the signals and the road conditions, the vehicle controller send the signals back to the two motor controllers to control the toque of each motor in order to adjust the real speeds of the rear wheels.…”

Section: Introductionmentioning

confidence: 99%

Modeling and simulation of electronic differential system for an electric vehicle with two-motor-wheel drive

Zhao

Zhang

Guan

2009

2009 IEEE Intelligent Vehicles Symposium

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In-wheel-motor drive electric vehicle (EV) is an innovative configuration, in which each wheel is driven individually by an electric motor. It is possible to use an electronic differential (ED) instead of the heavy mechanical differential because of the fast response time of the motor. A new ED control approach for a two-in-wheel-motor drive EV is devised based on the fuzzy logic control method. The fuzzy logic method employs to estimate the slip rate of each wheel considering the complex and nonlinear of the system. Then, the ED system distributes torque and power to each motor according to requirements. The effectiveness and validation of the proposed control method are evaluated in the Matlab/Simulink environment. Simulation results show that the new ED control system can keep the slip rate within the optimized range, ensuring the stability of the vehicle either in a straight or a curve lane.

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A Sensolrless Speed Control System for an Electric Vehicle without Mechanical Differential Gear

Cited by 17 publications

References 0 publications

Modeling, Analysis, and Neural Network Control of an EV Electrical Differential

Modeling, Analysis, and Neural Network Control of an EV Electrical Differential

Sensorless speed control of a permanent magnet DC motor by compensating the plant nonlinearities

Modeling and simulation of electronic differential system for an electric vehicle with two-motor-wheel drive

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