A Combined Cooperative Braking Model with a Predictive Control Strategy in an Electric Vehicle
Cooperative braking with regenerative braking and mechanical braking plays an important role in electric vehicles for energy-saving control. Based on the parallel and the series cooperative braking models, a combined model with a predictive control strategy to get a better cooperative braking perfor...
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Online Access: | http://www.mdpi.com/1996-1073/6/12/6455 |
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doaj-32584af1055f4cbbbd4918300891b5c72020-11-24T22:51:52ZengMDPI AGEnergies1996-10732013-12-016126455647510.3390/en6126455en6126455A Combined Cooperative Braking Model with a Predictive Control Strategy in an Electric VehicleHongqiang Guo0Hongwen He1Fengchun Sun2National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing 100081, ChinaNational Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing 100081, ChinaNational Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing 100081, ChinaCooperative braking with regenerative braking and mechanical braking plays an important role in electric vehicles for energy-saving control. Based on the parallel and the series cooperative braking models, a combined model with a predictive control strategy to get a better cooperative braking performance is presented. The balance problem between the maximum regenerative energy recovery efficiency and the optimum braking stability is solved through an off-line process optimization stream with the collaborative optimization algorithm (CO). To carry out the process optimization stream, the optimal Latin hypercube design (Opt LHD) is presented to discrete the continuous design space. To solve the poor real-time problem of the optimization, a high-precision predictive model based on the off-line optimization data of the combined model is built, and a predictive control strategy is proposed and verified through simulation. The simulation results demonstrate that the predictive control strategy and the combined model are reasonable and effective.http://www.mdpi.com/1996-1073/6/12/6455electric vehiclescooperative brakingcombined modelcollaborative optimization algorithmpredictive control strategy |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Hongqiang Guo Hongwen He Fengchun Sun |
spellingShingle |
Hongqiang Guo Hongwen He Fengchun Sun A Combined Cooperative Braking Model with a Predictive Control Strategy in an Electric Vehicle Energies electric vehicles cooperative braking combined model collaborative optimization algorithm predictive control strategy |
author_facet |
Hongqiang Guo Hongwen He Fengchun Sun |
author_sort |
Hongqiang Guo |
title |
A Combined Cooperative Braking Model with a Predictive Control Strategy in an Electric Vehicle |
title_short |
A Combined Cooperative Braking Model with a Predictive Control Strategy in an Electric Vehicle |
title_full |
A Combined Cooperative Braking Model with a Predictive Control Strategy in an Electric Vehicle |
title_fullStr |
A Combined Cooperative Braking Model with a Predictive Control Strategy in an Electric Vehicle |
title_full_unstemmed |
A Combined Cooperative Braking Model with a Predictive Control Strategy in an Electric Vehicle |
title_sort |
combined cooperative braking model with a predictive control strategy in an electric vehicle |
publisher |
MDPI AG |
series |
Energies |
issn |
1996-1073 |
publishDate |
2013-12-01 |
description |
Cooperative braking with regenerative braking and mechanical braking plays an important role in electric vehicles for energy-saving control. Based on the parallel and the series cooperative braking models, a combined model with a predictive control strategy to get a better cooperative braking performance is presented. The balance problem between the maximum regenerative energy recovery efficiency and the optimum braking stability is solved through an off-line process optimization stream with the collaborative optimization algorithm (CO). To carry out the process optimization stream, the optimal Latin hypercube design (Opt LHD) is presented to discrete the continuous design space. To solve the poor real-time problem of the optimization, a high-precision predictive model based on the off-line optimization data of the combined model is built, and a predictive control strategy is proposed and verified through simulation. The simulation results demonstrate that the predictive control strategy and the combined model are reasonable and effective. |
topic |
electric vehicles cooperative braking combined model collaborative optimization algorithm predictive control strategy |
url |
http://www.mdpi.com/1996-1073/6/12/6455 |
work_keys_str_mv |
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_version_ |
1725668410278281216 |