TY - GEN
T1 - Reducing NOx Emissions and Optimizing Fuel Economy by Controlling Torque and Catalyst warm-up in mild HEVs
AU - Umezawa, Yuka
AU - Seto, Hiroki
AU - Imamura, Toshiro
AU - Namerikawa, Toru
N1 - Publisher Copyright:
© 2022 ACA.
PY - 2022
Y1 - 2022
N2 - In this paper, hierarchical model predictive control is applied to mild HEVs in order to improve fuel economy and reduce NOx emissions. There is a difference in the timescale between the temperature control (high-level) and the torque control (low-level), which are connected problems via the battery. In high-level of the hierarchical control, the optimal amount of heating from the battery to the catalyst in the exhaust gas after-treatment system is determined. The amount of heating must be determined in such a way that the catalyst can optimally purify NOx emitted from the engine. At the low-level of the hierarchical control, the optimal torque distribution for the engine and motor is determined. The controller at both levels then applies model predictive control to account for the future behavior of the HEV's components. Fuel consumption, battery SoC and NOx emissions from the engine are taken into account. Finally, the effectiveness of our proposed method is demonstrated by simulations.
AB - In this paper, hierarchical model predictive control is applied to mild HEVs in order to improve fuel economy and reduce NOx emissions. There is a difference in the timescale between the temperature control (high-level) and the torque control (low-level), which are connected problems via the battery. In high-level of the hierarchical control, the optimal amount of heating from the battery to the catalyst in the exhaust gas after-treatment system is determined. The amount of heating must be determined in such a way that the catalyst can optimally purify NOx emitted from the engine. At the low-level of the hierarchical control, the optimal torque distribution for the engine and motor is determined. The controller at both levels then applies model predictive control to account for the future behavior of the HEV's components. Fuel consumption, battery SoC and NOx emissions from the engine are taken into account. Finally, the effectiveness of our proposed method is demonstrated by simulations.
KW - Energy Management
KW - Hierarchical Control
KW - Model Predictive Control
KW - mild HEV
UR - http://www.scopus.com/inward/record.url?scp=85135614303&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85135614303&partnerID=8YFLogxK
U2 - 10.23919/ASCC56756.2022.9828204
DO - 10.23919/ASCC56756.2022.9828204
M3 - Conference contribution
AN - SCOPUS:85135614303
T3 - ASCC 2022 - 2022 13th Asian Control Conference, Proceedings
SP - 1914
EP - 1919
BT - ASCC 2022 - 2022 13th Asian Control Conference, Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 13th Asian Control Conference, ASCC 2022
Y2 - 4 May 2022 through 7 May 2022
ER -