Pregled bibliografske jedinice broj: 1085931
Optimal energy management and shift scheduling control of a parallel plug-in hybrid electric vehicle
Optimal energy management and shift scheduling control of a parallel plug-in hybrid electric vehicle // International Journal of Powertrains, 9 (2020), 3; 240-264 doi:10.1504/IJPT.2020.109666 (međunarodna recenzija, članak, znanstveni)
CROSBI ID: 1085931 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Optimal energy management and shift scheduling
control of a parallel plug-in hybrid electric
vehicle
Autori
Soldo, Jure ; Škugor, Branimir ; Deur, Joško
Izvornik
International Journal of Powertrains (1742-4267) 9
(2020), 3;
240-264
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
energy management ; equivalent consumption minimisation strategy ; ECMS ; shift scheduling ; control ; plug-in hybrid electric vehicle ; PHEV.
Sažetak
This paper deals with design of a control strategy for a parallel powertrain configuration of a plug-in hybrid electric vehicle (PHEV). The control strategy is aimed at minimising fuel consumption and number of gear shift events for a wide range of driving cycles, while keeping the battery state-of-charge within allowable range. A control-oriented backward-looking model of PHEV powertrain is used as a design basis. The control strategy combines a rule-based controller with an equivalent consumption minimisation strategy (ECMS). The ECMS uses both transmission gear ratio and engine torque as control variables, thus eliminating a need for designing a separate gear shift scheduling strategy and exploiting a full potential of powertrain efficiency improvement. The overall control strategy is designed for different characteristic operating regimes including charge depleting, charge sustaining, and blended regimes. The strategy is verified by computer simulations against globally optimal benchmark obtained by using the dynamic programming-based optimisation, whose results are also used for fine tuning of controller parameters.
Izvorni jezik
Engleski
Znanstvena područja
Strojarstvo
POVEZANOST RADA
Projekti:
IP-2018-01-8323 - Adaptivno i prediktivno upravljanje utičnim hibridnim električnim vozilima (ACHIEVE) (Deur, Joško, HRZZ - 2018-01) ( CroRIS)
Ustanove:
Fakultet strojarstva i brodogradnje, Zagreb
Citiraj ovu publikaciju:
Časopis indeksira:
- Scopus