Research On Regenerative Braking Energy Recovery Strategy For Hybrid Electric Vehicle

Science and technology makes automotive industry develop fast, which brings the lifeconvenient to people, however it also has caused some serious problems, such asenvironmental pollution and global warming, which threat to the survival of the humansociety. Governments around the world are planning out the development strategy of energyconservation and environmental protection. New energy vehicles have become a developmenttrend of automobile industry inevitably. Hybrid electric vehicles as one of the most importantrepresentatives of new energy vehicles, which has the regenerative braking technology toresolve these problems, and can recycle some traditional car loss of energy in the braking, soit can greatly improve the fuel economy of the car and save energy.Firstly, the dissertation introduces the research status and working principle of theregenerative braking of electric vehicle technology at home and abroad, and its influencingfactors. Secondly, it analyzes the energy storage principle of the regenerative braking energyrecovery system, and the mechanical analysis of automobile brake, meanwhile it calculatesthe size of the regenerative braking force. At the same time, the original two kinds of brakingenergy recovery strategies are briefly described, and the dissertation analyzes the advantagesand disadvantages of them. This dissertation has integrated the existing allocation method andcharacteristics, and studied the braking force allocation strategy of fuzzy logic system, finallyto improve the proposed regenerative braking force allocation strategy based on fuzzy neuralnetwork. Dissertation studies the front-wheel drive under the parallel hybrid electric vehicle,on the basis of meeting the braking regulations, as much as possible for automobile front axlebear most of the braking force, at the same time to ensure the safety and stability of thebraking, so that more braking energy is recycled.The proposed of braking force allocation strategy of this dissertation is verified throughadvanced vehicle simulation software ADVISOR2002. Experimental condition chooses theAmerican city driving cycles, the New York City driving cycles and the Japanese city ofdriving cycles to simulate verification, and contrasts to the allocation strategy of vehiclesimulation software and fuzzy logic allocation strategy. Experimental results show that thebraking force allocation strategy of fuzzy neural network system, on the premise ofguaranteeing the braking safety and stability, which can recycle more braking energy, andimprove the efficiency of the vehicle system, at the same time further verifying theeffectiveness of the feasibility and effectiveness of the proposed regenerative braking force allocation strategy in this dissertation.