Pregled bibliografske jedinice broj: 1133794
Analysis of optimal battery state-of-charge trajectory patterns for blended mode of a parallel plug-in hybrid electric vehicle and a wide range of driving conditions
Analysis of optimal battery state-of-charge trajectory patterns for blended mode of a parallel plug-in hybrid electric vehicle and a wide range of driving conditions // Optimization and engineering, 22 (2021), 1; 1-23 doi:10.1007/s11081-021-09656-6 (međunarodna recenzija, članak, znanstveni)
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Naslov
Analysis of optimal battery state-of-charge
trajectory patterns for blended mode of a
parallel plug-in hybrid electric vehicle and a
wide range of driving conditions
Autori
Soldo, Jure ; Škugor, Branimir ; Deur, Joško
Izvornik
Optimization and engineering (1389-4420) 22
(2021), 1;
1-23
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
Plug-in hybrid electric vehicle ; Power management ; Battery stateof- charge trajectory ; Energy efficiency ; Optimization ; Dynamic programming ; Analysis
Sažetak
In Plug-in hybrid electric vehicles (PHEVs) typically combine several power sources, which are coordinated by means of an optimal energy management strategy. When considering the so-called blended mode, in which the engine is regularly used over a trip, the shape of battery state- of-charge (SoC) trajectory over travelled distance is of particular importance for achieving minimum fuel consumption. The paper deals with in-depth analysis of optimal SoC trajectories obtained by off-line control variable optimization of a PHEV-type city bus given in parallel (P2) powertrain configuration. The optimization is conducted by using a dynamic programming- based optimization algorithm for a wide range of driving cycles and operating scenarios. It is found that, as opposed to usually assumed linear-like near-optimal shape, the SoC vs. travelled distance trajectory can take on significantly different optimal shapes for non-zero road grade profiles or driving cycle with relatively long distance. The emphasis is on analyzing root causes for such behavior and its implications to fuel consumption.
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