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    Intelligent Setpoint Optimization for a Range Extender Hybrid Electric Vehicle With Opposed Piston Engine

    Source: Journal of Dynamic Systems, Measurement, and Control:;2023:;volume( 146 ):;issue: 002::page 21003-1
    Author:
    Drallmeier, Joseph A.
    ,
    Nazari, Shima
    ,
    Solbrig, Charles
    ,
    Middleton, Robert
    ,
    Siegel, Jason
    DOI: 10.1115/1.4063799
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: This paper presents the exploration and optimization of a hybridized opposed piston (OP) engine. In this work, the exhaust crankshaft lead (ECL) is introduced as a controllable parameter in the hybridized OP engine enabled by eliminating the conventional geartrain linking the two crankshafts of an OP engine. This allows for variation in the effective compression and expansion ratio of the engine, along with scavenging performance. This novel control actuator as well as the adjustable speed and load setpoint in a series hybrid OP engine powertrain architecture necessitates an intensive calibration effort to realize any possible efficiency improvements. However, the OP engine within this series hybrid powertrain does not need to operate in highly transient conditions, but rather its operating point is fixed or slowly varying. This property permits the use of online calibration techniques. After manually sweeping speed and ECL values at two power setpoints, the use of an extremum-seeking type intercycle optimization algorithm to optimize the operating setpoint is validated, showing that near optimal speed and ECL setpoints can be selected despite the relatively flat operating map of the OP engine.
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      Intelligent Setpoint Optimization for a Range Extender Hybrid Electric Vehicle With Opposed Piston Engine

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4295999
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    • Journal of Dynamic Systems, Measurement, and Control

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    contributor authorDrallmeier, Joseph A.
    contributor authorNazari, Shima
    contributor authorSolbrig, Charles
    contributor authorMiddleton, Robert
    contributor authorSiegel, Jason
    date accessioned2024-04-24T22:51:29Z
    date available2024-04-24T22:51:29Z
    date copyright12/6/2023 12:00:00 AM
    date issued2023
    identifier issn0022-0434
    identifier otherds_146_02_021003.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4295999
    description abstractThis paper presents the exploration and optimization of a hybridized opposed piston (OP) engine. In this work, the exhaust crankshaft lead (ECL) is introduced as a controllable parameter in the hybridized OP engine enabled by eliminating the conventional geartrain linking the two crankshafts of an OP engine. This allows for variation in the effective compression and expansion ratio of the engine, along with scavenging performance. This novel control actuator as well as the adjustable speed and load setpoint in a series hybrid OP engine powertrain architecture necessitates an intensive calibration effort to realize any possible efficiency improvements. However, the OP engine within this series hybrid powertrain does not need to operate in highly transient conditions, but rather its operating point is fixed or slowly varying. This property permits the use of online calibration techniques. After manually sweeping speed and ECL values at two power setpoints, the use of an extremum-seeking type intercycle optimization algorithm to optimize the operating setpoint is validated, showing that near optimal speed and ECL setpoints can be selected despite the relatively flat operating map of the OP engine.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleIntelligent Setpoint Optimization for a Range Extender Hybrid Electric Vehicle With Opposed Piston Engine
    typeJournal Paper
    journal volume146
    journal issue2
    journal titleJournal of Dynamic Systems, Measurement, and Control
    identifier doi10.1115/1.4063799
    journal fristpage21003-1
    journal lastpage21003-11
    page11
    treeJournal of Dynamic Systems, Measurement, and Control:;2023:;volume( 146 ):;issue: 002
    contenttypeFulltext
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