A Smart Torque Control for a High Efficiency 4WD Electric Vehicle

2019 ◽  
pp. 213-219
Author(s):  
Antonio Cordopatri ◽  
Giuseppe Cocorullo
Keyword(s):  
Electric Vehicle ◽  
High Efficiency ◽  
Torque Control

Energy Optimal Control of Induction Motor for Electric Vehicle Drive System Base DTC

2014 ◽  
Vol 1046 ◽  
pp. 215-218
Author(s):  
Hong Xia Yu ◽  
Jing Shi Qiao
Keyword(s):  
Optimal Control ◽  
Induction Motor ◽  
Electric Vehicle ◽  
High Efficiency ◽  
Direct Torque Control ◽  
Operating Conditions ◽  
Drive System ◽  
Torque Control ◽  
Maximum Efficiency ◽  
Stator Flux

The requirements of the drive system for electric vehicle is high efficiency and fast dynamic response, an optimal control method base direct torque control is proposed to improve respose speed of energy optimal controlled induction motor. In stator flux orientation coordinate system, the loss mathematical model of the induction motor was established by analyzing the relationship between loss and motor torque, speed and stator flux, then the optimal stator flux formula is derived under different operating conditions to achieve the maximum efficiency of induction motor, the getted optimal stator flux is used as stator flux set value in DTC. Simulation results reveal that the proposed method improve the efficiency and respose spee of induction motor.

scholarly journals Design of Adaptive Fuzzy PI Controller for Electric Vehicle with BLDC Drives

2019 ◽  
Vol 8 (11) ◽  
pp. 2479-2483
Keyword(s):  
Electric Vehicle ◽  
Electric Motor ◽  
High Efficiency ◽  
Combustion Engine ◽  
Direct Torque Control ◽  
Torque Control ◽  
Control Technique ◽  
Adaptive Fuzzy ◽  
Brushless Dc ◽  
And Performance

Electric vehicles in concern with its innumerable advantages, replaces the internal combustion engine vehicles (ICEV). The efficiency and performance of the Electric Vehicle (EV) depends mainly on the electric motor and its control technique. The Brushless DC (BLDC) Motor is used as the electric motor in the EV as it has high efficiency and high starting torque. The sensorless direct torque control technique is used to enhance the performance of the EV. The Adaptive Fuzzy PI (AFPI) Controller is the proposed controller in the EV. The comparison of reference torque and actual torque produce the error. It is applied to the AFPI controller which produces an output of reference torque. The EV with stationary reference frame theory of direct torque control with AFPI controller is simulated using MATLAB/SIMULINK.

Driving Torque Control Method for Electric Vehicle with In-Wheel Motors

2011 ◽  
Vol 131 (5) ◽  
pp. 721-728 ◽  
Author(s):  
Masataka Yoshimura ◽  
Hiroshi Fujimoto
Keyword(s):  
Electric Vehicle ◽  
Control Method ◽  
Torque Control ◽  
Driving Torque

Proposal of 98.5% high-efficiency chopper circuit QRAS for the electric vehicle and the verification

2007 ◽  
Vol 158 (4) ◽  
pp. 68-80
Author(s):  
Yukinori Tsuruta ◽  
Atsuo Kawamura
Keyword(s):  
Electric Vehicle ◽  
High Efficiency

scholarly journals Novel Application of Fast Simulated Annealing Method in Brushless Motor Drive (BLMD) Dynamical Parameter Identification for Electric Vehicle Propulsion

2021 ◽  
Author(s):  
Richard A. Guinee
Keyword(s):  
Simulated Annealing ◽  
Parameter Identification ◽  
Electric Vehicle ◽  
Weight Ratio ◽  
Torque Control ◽  
Function Evaluation ◽  
Dynamical Parameter ◽  
Penalty Cost ◽  
Brushless Motor ◽  
Identification Strategy

Permanent magnet brushless motor drives (BLMD) are extensively used in electric vehicle (EV) propulsion systems because of their high power and torque to weight ratio, virtually maintenance free operation with precision control of torque, speed and position. An accurate dynamical parameter identification strategy is an essential feature in the adaptive control of such BLMD-EV systems where sensorless current feedback is employed for reliable torque control, with multi-modal penalty cost surfaces, in EV high performance tracking and target ranging. Application of the classical Powell Conjugate Direction optimization method is first discussed and its inaccuracy in dynamical parameter identification is illustrated for multimodal cost surfaces. This is used for comparison with the more accurate Fast Simulated Annealing/Diffusion (FSD) method, presented here, in terms of the returned parameter estimates. Details of the FSD development and application to the BLMD parameter estimation problem based on the minimum quantized parameter step sizes from noise considerations are provided. The accuracy of global parameter convergence estimates returned, cost function evaluation and the algorithm run time are presented. Validation of the FSD identification strategy is provided by excellent correlation of BLMD model simulation trace coherence with experimental test data at the optimal estimates and from cost surface simulation.

Research on Dynamic Torque Control Strategy for Parallel Hybrid Electric Vehicle

2011 ◽  
Vol 228-229 ◽  
pp. 951-956 ◽  
Author(s):  
Yun Bing Yan ◽  
Fu Wu Yan ◽  
Chang Qing Du
Keyword(s):  
Electric Vehicle ◽  
Hybrid Electric Vehicle ◽  
Control Algorithm ◽  
Dynamic Control ◽  
Torque Control ◽  
Engine Torque ◽  
Parallel Hybrid Electric Vehicle ◽  
Torque Control Strategy ◽  
Parallel Hybrid ◽  
Hybrid Electric

It is necessary for Parallel Hybrid Electric Vehicle (PHEV) to distribute energy between engine and motor and to control state-switch during work. Aimed at keeping the total torque unchanging under state-switch, the dynamic torque control algorithm is put forward, which can be expressed as motor torque compensation for engine after torque pre-distribution, engine speed regulation and dynamic engine torque estimation. Taking Matlab as the platform, the vehicle control simulation model is built, based on which the fundamental control algorithm is verified by simulation testing. The results demonstrate that the dynamic control algorithm can effectively dampen torque fluctuations and ensures power transfer smoothly under various state-switches.

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