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The Research On Control Strategy Of Plug-in Bus Based On Traffic Recognition

Posted on:2018-06-20Degree:MasterType:Thesis
Country:ChinaCandidate:W WangFull Text:PDF
GTID:2322330542961927Subject:Vehicle engineering
Abstract/Summary:PDF Full Text Request
The plug in buses are widely used as new energy buses in china now.They are able to use both the power grid and the engine to power the vehicle,so can reducing fuel ependence,and reducing operating costs and extending mileage.In the current vehicle control vehicle traffic impact did not fully consider the strategy research,so in the practical application of vehicle energy management strategy based on road identification,and has important significance to further enhance the vehicle economy.This paper taking the plug-in bus as the research object,in order to improve the economic operation of the vehicles in the traffic in the city for the purpose,the energy management strategy based on road identification were studied,the specific work is as follows:(1)The dynamic model of the vehicle was modeled.In order to solve the parameter matching optimization of complex nonlinear equations for the optimal solutions of the problem,the introduction of BP neural network and genetic algorithm to optimize the parameters,and provides the basis for parameter setting and working range of vehicle control.(2)The driver behavior and traffic behavior investigation of driver operation were analyzed to extract the operation rules of driving in city traffic,to provide a basis for the energy management strategy based on road identification,strengthen the applicability of the control strategy.(3)To obtain real-time traffic,the development of real-time traffic identification method based on driver behavior,while the use of the car networking cloud smart "to learn and recognize the specific sections,based on the recognition of traffic on the design of intelligent vehicle mode switching,and the introduction of vehicle energy management,improve the fuel economy of the vehicle and traffic adaptability.(4)To make APU work at the best fuel efficiency range,the design of APU intelligent learning algorithm,by changing the load to design the climbing method to find the best efficiency point,realize the power generation efficiency of the APU system to improve and enhance the fuel economy of the APU system.
Keywords/Search Tags:plug in model, driver model, road condition identification, fuel economy
PDF Full Text Request
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