Energy Recovery Strategy Numerical Simulation for Dual Axle Drive Pure Electric Vehicle Based on Motor Loss Model and Big Data Calculation

Aiming at the braking energy feedback control in the optimal energy recovery of the two-motor dual-axis drive electric vehicle (EV), the efficiency numerical simulation model based on the permanent magnet synchronous motor loss was established. At the same time, under different speed and braking con...

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Main Authors: Huiyuan Xiong, Xionglai Zhu, Ronghui Zhang
Format: Article
Language:English
Published: Wiley 2018-01-01
Series:Complexity
Online Access:http://dx.doi.org/10.1155/2018/4071743
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author Huiyuan Xiong
Xionglai Zhu
Ronghui Zhang
author_facet Huiyuan Xiong
Xionglai Zhu
Ronghui Zhang
author_sort Huiyuan Xiong
collection DOAJ
description Aiming at the braking energy feedback control in the optimal energy recovery of the two-motor dual-axis drive electric vehicle (EV), the efficiency numerical simulation model based on the permanent magnet synchronous motor loss was established. At the same time, under different speed and braking conditions, based on maximum recovery efficiency and data calculation of motor system, the optimization motor braking torque distribution model was established. Thus, the distribution rule of the power optimization for the front and rear electric mechanism was obtained. This paper takes the Economic Commission of Europe (ECE) braking safety regulation as the constraint condition, and finally, a new regenerative braking torque distribution strategy numerical simulation was developed. The simulation model of Simulink and CarSim was established based on the simulation object. The numerical simulation results show that under the proposed strategy, the average utilization efficiency of the motor system is increased by 3.24% compared with the I based braking force distribution strategy. Moreover, it is 9.95% higher than the maximum braking energy recovery strategy of the front axle. Finally, through the driving behavior of the driver obtained from the big data platform, we analyze how the automobile braking force matches with the driver’s driving behavior. It also analyzes how the automobile braking force matches the energy recovery efficiency. The research results in this paper provide a reference for the future calculation of braking force feedback control system based on big data of new energy vehicles. It also provides a reference for the modeling of brake feedback control system.
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institution Kabale University
issn 1076-2787
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language English
publishDate 2018-01-01
publisher Wiley
record_format Article
series Complexity
spelling doaj-art-6f2dafd3d3594f27bc4a90649286ad802025-08-20T03:34:05ZengWileyComplexity1076-27871099-05262018-01-01201810.1155/2018/40717434071743Energy Recovery Strategy Numerical Simulation for Dual Axle Drive Pure Electric Vehicle Based on Motor Loss Model and Big Data CalculationHuiyuan Xiong0Xionglai Zhu1Ronghui Zhang2School of Intelligent Systems Engineering, Sun Yat-sen University, Guangzhou, Guangdong 510006, ChinaSchool of Intelligent Systems Engineering, Sun Yat-sen University, Guangzhou, Guangdong 510006, ChinaSchool of Intelligent Systems Engineering, Sun Yat-sen University, Guangzhou, Guangdong 510006, ChinaAiming at the braking energy feedback control in the optimal energy recovery of the two-motor dual-axis drive electric vehicle (EV), the efficiency numerical simulation model based on the permanent magnet synchronous motor loss was established. At the same time, under different speed and braking conditions, based on maximum recovery efficiency and data calculation of motor system, the optimization motor braking torque distribution model was established. Thus, the distribution rule of the power optimization for the front and rear electric mechanism was obtained. This paper takes the Economic Commission of Europe (ECE) braking safety regulation as the constraint condition, and finally, a new regenerative braking torque distribution strategy numerical simulation was developed. The simulation model of Simulink and CarSim was established based on the simulation object. The numerical simulation results show that under the proposed strategy, the average utilization efficiency of the motor system is increased by 3.24% compared with the I based braking force distribution strategy. Moreover, it is 9.95% higher than the maximum braking energy recovery strategy of the front axle. Finally, through the driving behavior of the driver obtained from the big data platform, we analyze how the automobile braking force matches with the driver’s driving behavior. It also analyzes how the automobile braking force matches the energy recovery efficiency. The research results in this paper provide a reference for the future calculation of braking force feedback control system based on big data of new energy vehicles. It also provides a reference for the modeling of brake feedback control system.http://dx.doi.org/10.1155/2018/4071743
spellingShingle Huiyuan Xiong
Xionglai Zhu
Ronghui Zhang
Energy Recovery Strategy Numerical Simulation for Dual Axle Drive Pure Electric Vehicle Based on Motor Loss Model and Big Data Calculation
Complexity
title Energy Recovery Strategy Numerical Simulation for Dual Axle Drive Pure Electric Vehicle Based on Motor Loss Model and Big Data Calculation
title_full Energy Recovery Strategy Numerical Simulation for Dual Axle Drive Pure Electric Vehicle Based on Motor Loss Model and Big Data Calculation
title_fullStr Energy Recovery Strategy Numerical Simulation for Dual Axle Drive Pure Electric Vehicle Based on Motor Loss Model and Big Data Calculation
title_full_unstemmed Energy Recovery Strategy Numerical Simulation for Dual Axle Drive Pure Electric Vehicle Based on Motor Loss Model and Big Data Calculation
title_short Energy Recovery Strategy Numerical Simulation for Dual Axle Drive Pure Electric Vehicle Based on Motor Loss Model and Big Data Calculation
title_sort energy recovery strategy numerical simulation for dual axle drive pure electric vehicle based on motor loss model and big data calculation
url http://dx.doi.org/10.1155/2018/4071743
work_keys_str_mv AT huiyuanxiong energyrecoverystrategynumericalsimulationfordualaxledrivepureelectricvehiclebasedonmotorlossmodelandbigdatacalculation
AT xionglaizhu energyrecoverystrategynumericalsimulationfordualaxledrivepureelectricvehiclebasedonmotorlossmodelandbigdatacalculation
AT ronghuizhang energyrecoverystrategynumericalsimulationfordualaxledrivepureelectricvehiclebasedonmotorlossmodelandbigdatacalculation