Multi-target energy management strategy weight factor dynamic matching method, system and application

The invention belongs to the technical field of fuel cell energy management, and discloses a multi-target energy management strategy weight factor dynamic matching method and system and application, and the method comprises the steps: employing a fuzzy C clustering method to classify driving cycle s...

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Bibliographische Detailangaben
Hauptverfasser:	MA RUI, YANG YAPENG, GUO-YAN SIQI, ZHOU YANG, YANG FAN, JIANG WENTAO, MA RUIQING, CHEN BO
Format:	Patent
Sprache:	chi ; eng
Schlagworte:	BASIC ELECTRIC ELEMENTS CALCULATING COMPUTING COUNTING DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES ELECTRIC DIGITAL DATA PROCESSING ELECTRIC EQUIPMENT OR PROPULSION OF ELECTRICALLY-PROPELLEDVEHICLES ELECTRICITY ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES, IN GENERAL MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES PERFORMING OPERATIONS PHYSICS PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSIONOF CHEMICAL INTO ELECTRICAL ENERGY SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR TRANSPORTING VEHICLES IN GENERAL
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Beschreibung
Zusammenfassung:	The invention belongs to the technical field of fuel cell energy management, and discloses a multi-target energy management strategy weight factor dynamic matching method and system and application, and the method comprises the steps: employing a fuzzy C clustering method to classify driving cycle states in an offline link; processing each item of the target function according to specifications and value ranges of the cells and the fuel cells, enabling the cells and the fuel cells to be in the same order of magnitude, and performing weight distribution; establishing a weight distribution Map graph in each driving state in an off-line manner by using a dynamic planning method, and selecting an optimal weight distribution result of each driving cycle state from the weight distribution Map graph; in the online link, fuzzy optimization is carried out according to the membership degree through a real-time mode recognition result, and finally real-time optimal weight distribution is obtained and input to a quadrati