Research On Regenerative Braking Of Three-axle Logistics Vehicle

With the continuous improvement of people’s awareness of environmental protection,stricter laws will be enforced.The development of high efficiency energy saving and environment-friendly vehicle becomes a major trend.Compared with traditional fuel vehicles,Hybrid cars retain the advantages of conventional fuel vehicles.Hybrid electric vehicle has the characteristics of long driving distance and good dynamic performance.At the same time,the fuel economy of the vehicle is greatly improved.It makes hybrid cars the most promising alternative fuel vehicles in the near future.Braking energy recovery system is the main contributor to the improvement of fuel economy of hybrid electric vehicle.Regenerative braking has become a key technology of hybrid electric vehicle.In the process of braking energy recovery,the coordination of multiple systems is involved.On the basis of hydraulic braking system,the addition of regenerative braking makes the braking system complicated.Brake safety,comfort,braking energy recovery efficiency need to be considered in a comprehensive manner,coordination and control of good hydraulic power and motor braking force to become the key.Because of the addition of the motor the flow of Hybrid electric vehicles energy is more convenient and efficient,the regenerative braking process is affected by many factors,and in the case of emergency-the braking energy recovery will be disabled.It is necessary to identify the driver’s emergency braking intention.The main contents of this paper are as follows:(1)According to the characteristics of the braking energy recovery system,based on the simulation software Trucksim,a new hybrid vehicle forward simulation model was built.It includes engine,clutch,transmission,motor,battery,two gear AMT model.This paper establishes the energy management strategy model with Stateflow to coordinate the work of each part of the power system.(2)In this paper,the distribution law of the braking force is analyzed,and the relation curve between the adhesion coefficient and the braking strength is transformed into the front and rear axle braking force distribution control line.This paper analyzes the typical regenerative braking control strategy,and puts forward the regenerative braking control strategy of hybrid electric vehicle.On the basis of the common braking energy recovery system,the paper studies the braking energy recovery based on the accelerator pedal.Selection of regenerative braking simulation conditions is used to find out the problems in the joint simulation of hybrid electric vehicle.After removing the effect of hybrid vehicle energy management strategy,the performance of braking energy recovery system is verified.(3)On the basis of the existing Lab VIEW RT platform,combined with the characteristics of MATLAB/Simulink and Trucksim,the test platform is established.With third party software interface provided by Lab VIEW RT,Trucksim vehicle model,Simulink power transmission system model and energy management strategy model,the hardware in the loop simulation test platform is established in the framwork of Lab VIEW RT.Vehicle information display interface and hybrid instrument panel interface is designed for convenient observation.The signal interaction among the modules,the acquisition of sensor signals and the storage of experimental data are completed.(4)According to the characteristics of the driver braking process,the Multidimensional Discrete Hidden Markov Model of braking intention is established,which is include emergency braking intention and smooth braking model.The experimental methods and experimental conditions will be selected,corresponding driver intent on vehicle handling data for model training is provided,and then MATLAB toolbox in HMM to train the model offline will be used.The hidden Markov intention recognition model written in MATLAB is embedded in the HIL test platform,the HIL of braking energy recovery system is tested,braking energy recovery system for energy-saving contribution and braking intention recognition accuracy can be analyzed.