TY - GEN
T1 - A finite-set model-based predictive battery thermal management in connected and automated hybrid electric vehicles
AU - Zhu, Chong
AU - Lu, Fei
AU - Zhang, Hua
AU - Zhu, Kangxi
AU - Mi, Chris
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/4/18
Y1 - 2018/4/18
N2 - The connected and automated hybrid electric vehicles (CAHEVs) have the potential to improve safety by mitigating traffic accidents. A crucial problem of the CAHEVs is that the Lithium-ion batteries are highly temperature-sensitive and may be premature aging at high working temperatures. Consequently, an effective and efficient battery thermal management (BTM) system is required with the minimum possible cooling energy consumption. To achieve the multiple objectives, a finite-set model-based (FSMB) predictive control strategy for the BTM in a CAHEV is presented, in which an improved cost function is proposed for better performances. Based on the predictive model of battery temperatures, the optimum cooling approach is determined with consideration of the future road information and battery charge/discharge power. The hardware-in-the-loop (HIL) test based on a Toyota Prius HEV model and the UDDS road cycle is conducted, and the results demonstrate the effectiveness of the proposed BTM strategy in both temperature control and energy saving.
AB - The connected and automated hybrid electric vehicles (CAHEVs) have the potential to improve safety by mitigating traffic accidents. A crucial problem of the CAHEVs is that the Lithium-ion batteries are highly temperature-sensitive and may be premature aging at high working temperatures. Consequently, an effective and efficient battery thermal management (BTM) system is required with the minimum possible cooling energy consumption. To achieve the multiple objectives, a finite-set model-based (FSMB) predictive control strategy for the BTM in a CAHEV is presented, in which an improved cost function is proposed for better performances. Based on the predictive model of battery temperatures, the optimum cooling approach is determined with consideration of the future road information and battery charge/discharge power. The hardware-in-the-loop (HIL) test based on a Toyota Prius HEV model and the UDDS road cycle is conducted, and the results demonstrate the effectiveness of the proposed BTM strategy in both temperature control and energy saving.
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U2 - 10.1109/APEC.2018.8341596
DO - 10.1109/APEC.2018.8341596
M3 - Conference contribution
AN - SCOPUS:85046943479
T3 - Conference Proceedings - IEEE Applied Power Electronics Conference and Exposition - APEC
SP - 3428
EP - 3433
BT - APEC 2018 - 33rd Annual IEEE Applied Power Electronics Conference and Exposition
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 33rd Annual IEEE Applied Power Electronics Conference and Exposition, APEC 2018
Y2 - 4 March 2018 through 8 March 2018
ER -