| As environmental pollution and energy exhaustion become worse and worse,it is a general trend to develop new energy vehicles and promote energy saving and emission reduction of automobiles.Pure electric vehicle(EV)has attracted widespread attention because of its pollution-free and high energy conversion efficiency.But the battery technology of EV is not yet mature,there is less energy per unit of weight storage,short running mileage and so on shortcomings,thus limiting the popularity of electric vehicles.Regenerative braking technology has become an effective means to improve the driving range of electric vehicles on the premise that it is difficult to make breakthrough progress in battery technology in the short term.Shifting during braking process can improve motor efficiency and regenerative braking torque,and increase the energy recovered from regenerative braking.The combination of regenerative braking and shifting can further improve the driving range of EV.In order to improve the economy,safety and comfort of EV during braking and shifting,this paper studies the shifting control of two-speed AMT of EV during braking.The main work of this paper is as follows:(1)Considering the influence of driving style on energy consumption economy,a fuzzy recognition method of driving style is proposed.The driving style is classified and the parameters of driving intention recognition are determined.The membership function and fuzzy reasoning rules of driving style fuzzy recognition are established.According to different driving styles,the corresponding regenerative braking force distribution algorithm is proposed.Taking two-speed AMT of EV as the research object,the power transmission system model and braking system model of the vehicle are built,including motor model,battery model,transmission model,regenerative braking model and hydraulic braking model.(2)In this paper,the dynamic characteristics of motor,transmission and hydraulic system during brake shifting are analyzed.By analyzing the characteristics of motor braking and hydraulic braking,and based on the braking force distribution strategy,a control strategy to coordinate the changes of motor braking force and hydraulic braking force is proposed to achieve the comfort of braking process.By analyzing the principle of regenerative braking,the low speed cut-off point(LSCP)of dynamic response regenerative braking is determined,which prolongs the regenerative braking process and increases the energy recovery rate of regenerative braking.By analyzing the shift process of two-speed AMT of EV,the control strategy of shift process considering both shift time and impact is worked out.The simulation results show that the braking shift process strategy can achieve the rapidity and comfort of braking shift.(3)In this paper,the braking force of the whole vehicle under braking condition is analyzed,and the regenerative braking moment of the motor under different gear and braking intensity is obtained.Taking vehicle speed,motor regenerative braking moment and braking strength as optimization variables,regenerative braking energy recovery and vehicle impact as optimization objectives,a multi-objective optimal shift law suitable for non-radical driving style is proposed.On the premise of ensuring braking stability,taking vehicle speed,motor regenerative braking moment and braking strength as optimization variables,regenerative braking energy recovery and vehicle impact as optimization objectives,a multi-objective optimal shift law suitable for power driving style is proposed.(4)The shift control strategy of two-speed AMT under braking condition is proposed.The simulation results show that the energy recovery strategy proposed in this paper improves the braking energy recovery compared with the energy recovery strategy without shifting,and the impact of shifting and vehicle safety meet the standards.At the same time,a hardware-in-the-loop experimental platform based on D2P-NI real-time simulator is built.D2 P is used as the real vehicle controller,and NI PXI is used as the carrier of the vehicle control object to verify the effectiveness of the proposed control strategy. |
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