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Study On Energy Management Strategy And Parameter Matching Of Parallel Hybrid Construction Machinery

Posted on:2013-12-20Degree:MasterType:Thesis
Country:ChinaCandidate:Y L JingFull Text:PDF
GTID:2232330371484398Subject:Mechanical engineering
Abstract/Summary:PDF Full Text Request
Today energy shortage and environmental pollution increasingly serious, loaderis a indispensable earthmoving equipment in mechanized construction, Because ofits large amount of high energy consumption, energy-saving research of loader hasimportant practical significance in the current society.In order to realize construction Machinery saving energy and reducing exhaustemissions,currently hybrid technology applied to construction machinery is animportant direction of construction mechanical field.But in our country,hybridtechnological application in construction mechanical field has just started.Developewith own intellectual property right of hybrid construction machinery,which plays animportant part in our future construction mechanical field.Study on loader energy-saving and parameters matching problem,should put thepower system of loader as the main research object. In this paper, after the structureof hybrid systems and parameters is determined, The real-time optimal strategy isproposed, and the hybrid system model is simulated,examined the real-time optimalstrategy control effect. Finally,genetic algorithm is used in the parameters optimizingof the hybrid system.The main contents of each chapter are summarized as follows:Chapter1Introduction.The background and meaning of the project is discussed,and development process and research status on the domestic and international ofloader and the application of Hybrid technology in the field of construction machineryis introduced. And this chapter analyzes the current application of Hybrid technologyin the field of construction machinery. The main research contents of this dissertationare proposed.Chapter2Study on hybrid system in loader.The power system structure of theloader and features are introduced,according to the load change in the actualoperation of the loader,this chapter analyzes the working characteristics of theload,Coaxial parallel hybrid system is finally determined by comparing the merits anddemerits of parallel and series hybrid system and the power system structuralcharacteristics of the loader.The main components’working characteristics of hybridsystem are Introduced. And compares the merits and demerits of different accumulators, Super capacitor is finally chosen as the energy storage device.Chapter3Study on control strategy of hybrid system in loader.Firstly,this chapterintroduces the current control strategies of hybrid system in the field of vehicle andconstruction machinery.According to the successful experience of theabove-mentioned fields and the specific characteristics of loader, the method thatreal-time optimal control strategy controlling the hybrid system of loader is proposed.According to state information of super capacitor’ electrical energy storage andconsumption, defines the future condition of energy consumption and the futurecondition of energy compensation,the SOC maintenance strategy of super capacitor isproposed.Finally this chapter establishes the objective function of real-time optimalcontrol strategy.Chapter4Simulation of hybrid system in loader.The parallel hybrid system andthe main components simulation model are established in this paper. Comparison therule-based logic threshold control strategy and the real-time optimal control strategy,Simulation results show that the real-time optimal control strategy is more significantand obvious in the fuel efficiency.Chapter5Parameter matching of hybrid system in loader.Using GeneticAlgorithm to optimize and match the control parameters of hybrid system in loader,fuel efficiency is improved. Fuel savings increase to10%, the goal of fuel savings isrealized.Chapter6Summary and outlook.It summarizes the main research achievementsof this paper, and looks forward to the further research work.
Keywords/Search Tags:Loader, Hybrid system, Real-time optimization, Control strategyParameter optimization, Genetic Algorithm
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