Research On Regenerative Braking Control Strategy Of Automated Guided Vehicle

In the current era of big data and artificial intelligence,production efficiency has been greatly improved,and production workshops have been gradually developed from traditional automation to intelligentization through digitalization.As a key equipment for intelligentization,the extensive application of Automated Guided Vehicle(AGV)is imperative.At present,most of AGVs use batteries as the power source,and adopt electric drive mode.Due to the driving conditions and battery charging and discharging characteristics,the driving range of the AGV is limited,and the working efficiency is not highly improved.It limits the production efficiency of enterprises.Therefore,it is of great significance to study ways to improve the energy utilization rate of the AGV and its driving range.In this thesis,a four-wheel drive AGV is taken as the research object,and the regenerative braking technology is applied to the braking system of the AGV.The regenerative braking control strategy suitable for AGV is designed.Firstly,the electric motor model,battery model and controller model of AGV are established by ADVISOR and MATLAB/Simulink software,and the dynamic performance of the vehicle is simulated by ADVISOR software.At the same time,the acceleration,driving range and other data of AGV are tested in real vehicle,and the simulation results are compared with the real vehicle test results to verify the validity of the AGV model.Secondly,the principle of regenerative braking system,energy flow in the braking process and the factors affecting energy recovery are analyzed in detail,and the braking force distribution of AGV under ideal braking conditions and ECE regulations are studied.Then the typical braking force distribution strategies are analyzed in detail,and based on this,the regenerative braking system based on fuzzy control is designed,and the simulation model of the control strategy is built by MATLAB/Simulink software.Then the evaluation criteria of energy recovery are established,and three kinds of drive cycles suitable for AGV are designed according to the operating characteristics of the AGV.Simulation analysis is carried out in ADVISOR software to compare the effects of different control strategies on energy recovery.The superiority of the braking force distribution strategy designed in this paper makes the energy feedback rate up to 54.79%,the battery SOC can be increased by 21.25%,the driving range is increased by 10.8 kilometers,and the current in the energy recovery process is monitored to guarantee the safety of the charge.Finally,according to the deficiencies in the design process of fuzzy controller,the genetic algorithm is used to optimize the membership function and fuzzy rules,and the fuzzy controller is re-established according to the optimization results.Simulation analysis is performed again in ADVISOR software.Compared with the control strategy before optimization,the battery SOC increased by 11.73% and driving range increased by 2.6km.Overall,the control strategy designed in this thesis can effectively improve the energy recovery during the braking process and improve the driving range of the AGV compared with the classic control strategies.