Synthesis And Characterization Of Organic/Inorganic Multifunctional Microspheres And Their Application For Optical Chemosensors And Bioimaging

Braking energy regeneration is one of the most effective ways of fuel-efficient forhybrid cars. The key technology of regenerative braking research has important realisticsignificance and application value.In order to ensure that the car brake well, at the same time, let the motor recycle as faras possible many braking energy, we should make the proper regenerative braking controlstrategy and make the distribution of electric braking and mechanical braking intensityreasonable. Make the vehicle to ensure the brake at the same time to maximize the recoveryof braking energy. Current control strategies research mainly concentrates in the motor andmechanical brake braking force distribution. The driver's braking intention identification isonly on the brake pedal opening this single parameter. The obtained results according to thedegree of brake pedal drive to identify braking intention are not accurate. Current controlstrategies while using a number of advanced control theory, but the control effect is justpassable.So, single brake pedal opening has been unable to meet the needs of regenerativebraking control. Multi parameter precise identification of braking intention on regenerativebraking control is of great significance. On one hand, according to the actual driver brakingintention to distribute the motor braking and the mechanical braking more reasonable. Notonly can ensure the vehicle braking and can make the motor recovery more braking energy.On the other hand, can guarantee the automobile coasting distance. Improve the drivingperformance under the premise of coasting brake energy recovery.This task group shared" hybrid vehicle control strategy research" project with FAW R &D center in863hybrid vehicle development projects. Origin of the subject is the driverintention recognition module of the key technology in the project--auxiliary control module.Intention recognition is divided into driver intention recognition and braking intentionrecognition. The content of this paper is the braking intention recognition and controlalgorithm. The paper carried out the following works:First, analysis and study of lots of vehicle condition data, and make the classificationand characterization of braking intention.In second, MATLAB is used to establish the fuzzy identification model to identify theconventional braking intention.Third, verify fuzzy identifier recognition effect online through the real vehicle road test.Use neural network to optimize the fuzzy membership function. Improved the recognitionaccuracy rate.In fourth, established a coasting brake V-t mathematical model and deduced thecoasting brake motor load rate control formula by analyzing the traditional car free slidingkinetic analysis, the driver's analysis and a large number of real vehicle sliding data statisticsfor The coasting braking intention recognition.Finally, optimized regenerative braking control strategy based on the braking intentionidentification. Then established a CRUISE-SIMULINK forward simulation platform, andthe control strategy was validated by simulation. Proofed of the optimization of controlstrategy for hybrid electric vehicle based on braking intention identification has played apositive role to driving performance and vehicle fuel economy.