This paper proposes a multi-dimensional size optimization framework and a hierarchical energy management strategy (HEMS) to optimize the component size and the power of a plug-in hybrid electric vehicle (PHEV) with the hybrid energy storage system (HESS). In order to evaluate the performance of size optimization and power optimization, a PHEV with a battery energy storage system (BESS) is used as a comparison reference, and the dynamic programming (DP) algorithm is set as a benchmark for comparison. The size optimization method explores the optimal configuration of the system, including the maximum power of the system, the maximum power and capacity of the battery, and the maximum power and capacity of the supercapacitor (SC). Compared with the BESS, the size-optimized HESS reduces the capacity of the system by 31.3% and improves the economy by 37.8%. The HEMS can simultaneously optimize vehicle fuel consumption and suppress battery aging. Its upper layer uses the DP algorithm to optimize fuel economy, and the lower layer apply the linear programming (LP) method to improve battery life. Based on the size optimization results and HEMS, compared with the benchmark, the battery aging rate has been reduced by 48.9%, and the vehicle economy has increased by 21.2%.
|Number of pages||11|
|Early online date||3 Aug 2020|
|Publication status||Published - 14 Aug 2020|
Bibliographical noteThis is an Open Access article distributed under the terms of the Creative
Commons Attribution License (http://creativecommons.org/licenses/by/4.0/),
which permits unrestricted use, distribution, and reproduction in any medium,
provided the original work is properly cited..
FunderThis work was supported by the Nature Science Foundation of China under Grant 51807008 and Grant U1864202.
- Battery life improvement
- hybrid energy storage system
- plug-in hybrid electric vehicle
- power optimization
- size optimization
ASJC Scopus subject areas
- Computer Science(all)
- Materials Science(all)