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PHIL Implementation of Energy Management Optimization for a Parallel HEV on a Predefined Route
61
Citations
24
References
2011
Year
Mathematical ProgrammingReal-time ControlEngineeringEnergy EfficiencyHybrid Electric VehicleReal-time Energy ManagementPowertrain SimulationParallel MetaheuristicsOptimal System DesignReal-time MethodsEnergy Management OptimizationEnergy OptimizationSystems EngineeringParallel ComputingCombinatorial OptimizationRenewable Energy SystemsParallel HevElectrical EngineeringComputer EngineeringPower System OptimizationHybrid Energy SystemHybrid VehiclePhil ImplementationEnergy OperationEnergy ManagementBattery ConfigurationParallel ProgrammingGrid OptimizationEnergy Economics
Real-time energy management of hybrid electric vehicles (HEVs) is a key point for performing effective fuel economy optimization. Offline methods have been developed for energy management optimization when the drive cycle is known. Online real-time methods can provide good results but can only ensure suboptimal management. In this paper, it is assumed that information about the route is available in advance. Using this knowledge, global optimization methods can be used in real-time control to approach optimal fuel consumption while keeping the state of charge <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex Notation="TeX">$(Soc)$</tex></formula> of the batteries at a desired level. Such a method is presented in this paper. The developed strategy is implemented in a real-time experiment using the power-hardware-in-the-loop (PHIL) principle. The measured fuel consumption and the obtained battery <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex Notation="TeX">$Soc$</tex></formula> trajectory demonstrate good performance of the proposed control.
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