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Power management op...
Power management optimization in plug-in hybrid electric vehicles subject to uncertain driving cycles
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- Zhang, Hongtao (författare)
- Univ Waterloo, Dept Mech & Mechatron Engn, Lab Fuel Cell & Green Energy RD&D 20 20, Waterloo, ON N2L 3G1, Canada.;Univ Waterloo, Dept Appl Math, Waterloo, ON N2L 3G1, Canada.,University of Waterloo, Waterloo, Canada
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- Qin, Yanzhou (författare)
- Univ Waterloo, Dept Mech & Mechatron Engn, Lab Fuel Cell & Green Energy RD&D 20 20, Waterloo, ON N2L 3G1, Canada.,University of Waterloo, Waterloo, Canada
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- Li, Xianguo (författare)
- Univ Waterloo, Dept Mech & Mechatron Engn, Lab Fuel Cell & Green Energy RD&D 20 20, Waterloo, ON N2L 3G1, Canada.,University of Waterloo, Waterloo, Canada
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- Liu, Xinzhi (författare)
- Univ Waterloo, Dept Appl Math, Waterloo, ON N2L 3G1, Canada.,University of Waterloo, Waterloo, Canada
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- Yan, Jinyue, 1959- (författare)
- Mälardalens högskola,KTH,Energiprocesser,Mälardalen Univ, Sch Sustainable Dev Soc & Technol, S-72123 Västerås, Sweden.,Framtidens energi
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Univ Waterloo, Dept Mech & Mechatron Engn, Lab Fuel Cell & Green Energy RD&D 20 20, Waterloo, ON N2L 3G1, Canada;Univ Waterloo, Dept Appl Math, Waterloo, ON N2L 3G1, Canada. University of Waterloo, Waterloo, Canada (creator_code:org_t)
- Elsevier BV, 2020
- 2020
- Engelska.
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Ingår i: eTransporation. - : Elsevier BV. - 2590-1168. ; 3
- Relaterad länk:
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https://doi.org/10.1...
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https://urn.kb.se/re...
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https://doi.org/10.1...
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https://urn.kb.se/re...
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Abstract
Ämnesord
Stäng
- Optimization of power management in plug-in hybrid electric vehicles (PHEVs) with dual-power-source plays a critical role in achieving higher fuel economy and less pollutant emissions. In this study, power management and optimal control strategies in PHEVs have been investigated subject to uncertain driving cycles of individual drivers for particular trips. First, a stochastic driving cycle is constructed to more accurately model the dynamic characteristics of the uncertain driving cycles, derived from the historic record of individual drivers. Finite-horizon stochastic dynamic programming is adapted to globally optimize the vehicle performance in stochastic sense. Simulation results show that the proposed strategy significantly improves fuel economy, indicating the present optimization approach is very effective in exploring the potential of the hybridization of power train. A higher discretization of (that is, with smaller step sizes in) vehicle dynamics state variables (vehicle velocity, power demand and battery state of charge) has a positive impact on the fuel economy while the limitation of driving operability actually degrades the fuel economy. The commuting time with doubly truncated normal distribution slightly enhances the fuel economy in comparison with uniform distribution. In addition, there exists a tradeoff between the fuel economy and the pollutant emissions. These results could be utilized as a guideline for the design of PHEVs with different objectives.
Ämnesord
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Reglerteknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Control Engineering (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Maskinteknik -- Energiteknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Mechanical Engineering -- Energy Engineering (hsv//eng)
Nyckelord
- Plug-in hybrid electric vehicles (PHEVs)
- Power split
- Power management
- Optimal control
- Stochastic dynamic programming
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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