TY - JOUR
T1 - Optimal Design of a Hybrid Energy Storage System in a Plug-In Hybrid Electric Vehicle for Battery Lifetime Improvement
AU - Bai, Yunfei
AU - Li, Jianwei
AU - He, Hongwen
AU - Santos, Ricardo Caneloi Dos
AU - Yang, Qingqing
N1 - Publisher Copyright:
© 2013 IEEE.
PY - 2020
Y1 - 2020
N2 - 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%.
AB - 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%.
KW - Battery life improvement
KW - hybrid energy storage system
KW - plug-in hybrid electric vehicle
KW - power optimization
KW - size optimization
UR - http://www.scopus.com/inward/record.url?scp=85090053150&partnerID=8YFLogxK
U2 - 10.1109/ACCESS.2020.3013596
DO - 10.1109/ACCESS.2020.3013596
M3 - Article
AN - SCOPUS:85090053150
SN - 2169-3536
VL - 8
SP - 142148
EP - 142158
JO - IEEE Access
JF - IEEE Access
M1 - 9154768
ER -