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Research On Control Strategy And Parameter Matching Of Powertrain For Hybrid Electric Bus

Posted on:2016-05-04Degree:MasterType:Thesis
Country:ChinaCandidate:Y M LiFull Text:PDF
GTID:2272330479955364Subject:Vehicle Engineering
Abstract/Summary:
The application of hybrid city buses is an important means to solve oil crisis and environmental pollution. The reasonable match of dynamic parameters and the design of energy management strategy can effectively improve vehicle fuel economy and reduce emissions. A LNG / electric hybrid city bus is selected as research object, and its main power components are analyzed and selected. The simulation platform for hybrid city bus is built on ADVISOR, and the model of engine, motor, power battery pack, and driving cycles are built. In order to match vehicle dynamic parameters, the concept of degree of hybridization is introduced. The effect of different degree of hybridization on vehicle performance is analyzed, the optimal degree of hybridization is selected, and the parameters of engine, motor, power battery are matched. Electric assist control strategy and fuzzy logic control strategy are analyzed and modeled on the base of analyses of present control strategies. The control strategies are simulated on the ADVISOR simulation platform. The results show that the fuzzy control strategy is better than the electric assist control strategy on fuel consumption. Based on the data that are matched, prototypes of LNG / electric hybrid city bus are produced. According to relevant standards, the performance of these hybrid electric buses is tested, and the test result show that it is similar to the simulation result and vehicle fuel consumption is low. The performance of hybrid electric buses is tested on five bus lines and the real-time monitoring system for city buses is established to collect relevant date. The result show that the acceleration performance of LNG / electric hybrid city bus achieves design standards and fuel economy is excellent.
Keywords/Search Tags:LNG / electric hybrid buses, Parameter matching, Control strategy, Simulation, Vehicle testing
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