TY - GEN
T1 - A battery management system using nonlinear model predictive control for a hybrid electric vehicle
AU - Yu, Kaijiang
AU - Mukai, Masakazu
AU - Kawabe, Taketoshi
N1 - Funding Information:
⋆ This work has been supported by the Technical Committee on Automotive Control and Model Research (JSAE and SICE Joint).
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2013
Y1 - 2013
N2 - This present paper introduces a battery management system using nonlinear model predictive control for a hybrid electric vehicle. This paper adds two new contributions to this field. First, the apparent relationship between the battery power and the future road load is addressed in the cost function of the fuel economy optimal control problem with a simplified hybrid electric vehicle energy management system model. Second, it examines quantitatively the effects of operating the engine along the best efficiency line of the engine with a continuously variable transmission using a commercially available hybrid electric vehicle energy management electronic control unit simulator. Effectiveness of the proposed algorithm is validated by the JSAE-SICE benchmark problem II simulator.
AB - This present paper introduces a battery management system using nonlinear model predictive control for a hybrid electric vehicle. This paper adds two new contributions to this field. First, the apparent relationship between the battery power and the future road load is addressed in the cost function of the fuel economy optimal control problem with a simplified hybrid electric vehicle energy management system model. Second, it examines quantitatively the effects of operating the engine along the best efficiency line of the engine with a continuously variable transmission using a commercially available hybrid electric vehicle energy management electronic control unit simulator. Effectiveness of the proposed algorithm is validated by the JSAE-SICE benchmark problem II simulator.
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U2 - 10.3182/20130904-4-JP-2042.00015
DO - 10.3182/20130904-4-JP-2042.00015
M3 - Conference contribution
AN - SCOPUS:84885929347
SN - 9783902823434
T3 - IFAC Proceedings Volumes (IFAC-PapersOnline)
SP - 301
EP - 306
BT - 7th IFAC Symposium on Advances in Automotive Control, AAC 2013 - Proceedings
PB - IFAC Secretariat
T2 - 7th IFAC Symposium on Advances in Automotive Control, AAC 2013
Y2 - 4 September 2013 through 7 September 2013
ER -