An ecms multi-objective two-layer optimization method with inner and outer layers nested

Abstract

The invention discloses an inner and outer layer nesting ECMS (equivalent fuel consumption minimization strategy) multi-objective double-layer optimization method. The inner and outer layer nesting ECMS multi-objective double-layer optimization method includes steps of building multi-objective optimization models of plug-in hybrid electric vehicles; solving the multi-objective optimization modelsby the aid of inner and outer layer nesting multi-objective particle swarm algorithms to obtain multi-objective optimized Pareto solution set front edges; weighting equivalent fuel consumption per hundred kilometers and variation ranges of deviation of SOC (state of charge) final values and target values, building total evaluation functions related to the equivalent fuel consumption per hundred kilometers and SOC deviation and selecting the optimal charge and discharge equivalent factors and engine and motor power distribution modes corresponding to the optimal charge and discharge equivalentfactors. The inner and outer layer nesting ECMS multi-objective double-layer optimization method has the advantages that output power of engines and motors of the plug-in hybrid electric vehicles canbe reasonably distributed at CS (charge sustaining) stages, so that fuel consumption can be reduced as much as possible, battery SOC balance still can be effectively kept, and the fuel economy of theintegral vehicles can be improved.

Description

technical field [0001] The invention relates to a multi-objective double-layer optimization method of an equivalent fuel consumption minimum energy management strategy nested with inner and outer layers, and belongs to the technical field of new energy vehicle control. Background technique [0002] The control idea of ​​equivalent fuel consumption minimization strategy (ECMS) is: according to the actual power requested by the driver of the vehicle, the actual output power of the engine and the motor is reasonably distributed within the power range of the engine and the motor, so that the engine instantaneous fuel consumption rate Equivalent fuel consumption rate of electric motor consumption The sum of is the smallest, as expressed by formulas (1) and (2): [0003] [0004] [0005] In the formula: is the total fuel consumption rate of the system at time t; is the instantaneous fuel consumption of the engine at time t, which can be obtained from the established...

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Problems solved by technology

Therefore, the optimization problem of ECMS is a discontinuous, non-conductive multi-objective optimization problem with inner and outer layer nesting. At present, there is no use of multi-objective intelligent bionic algorithm to optimize the charging and discharging equivalent factors and power distribution methods at the same time. Research

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