Research On Multimode Energy Management And Dynamic Coordination Control For Hydraulic Hub-Motor Hybrid System

Heavy commercial vehicles play an important role in the modernization infrastructure construction in China.Under the current background of broad market demand,strict fuel consumption limits and high vehicle comprehensive performance requirements,the development of high efficiency hybrid commercial vehicles has gradually become a common demand for the development of domestic commercial vehicle industry.The hydraulic hub-motor hybrid system(HHMHS),with its advantages of high power density,small mass,small volume and low cost,has shown strong competitiveness and good market application prospects in the field of heavy commercial vehicles.As a new type of hydraulic hybrid system,the HHMHS has good application potential,which can not only improve the passability of heavy vehicles on low-adhesion road significantly,but also improve the fuel economy through recycling regenerative braking energy by hydraulic accumulator when vehicle brakes,and can also improve braking safety by hydraulic auxiliary braking of accumulator.This paper was supported by the National Natural Science Foundation of China project "Multimode Dynamic Coordination and Nonlinear Control of Hydraulic Hub-motor Hybrid System for Heavy Commercial Vehicles"(Grant No.51675214).The multimode energy management strategy and the non-linear dynamic coordination control of the HHMHS were studied.Firstly,the simulation platform of the HHMHS is established based on MATLAB/Simulink software by using the parameter identification technology and the method of hydraulic chamber at node,which includes mechanical transmission path dynamics model and hydraulic transmission path dynamic model.The accuracy of the integrated model is verified by AMESim,a mature commercial software.And a good foundation of model simulation and test is provided for the development of multimode energy management and dynamic coordination control strategy.Secondly,a joint observation algorithm for driving conditions and key state parameters of heavy commercial vehicles is established,including road gradient estimation based on improved Kalman filter algorithm,longitudinal speed estimation based on kinematics method,model-based joint estimation of tire force and road adhesion coefficient and vehicle quality identification based on recursive least squares algorithm.By utilizing the easily accessible state information on the vehicle CAN bus and the collected information of the low-cost sensor,the accurate estimation of other state parameters,which are not suitable for direct acquisition,can be achieved.And the joint observation algorithm provides precise reference input for multimode energy management strategy.Thirdly,the theoretical fuel consumption calculation model of the HHMHS based on energy calculation is proposed.A novel concept of average comprehensive transmission efficiency is defined based on the internal energy flows of the HHMHS.And the theoretical fuel consumption model calculation is developed,which can not only calculate the fuel consumption from the macro energy perspective,but also quantitatively describe the effect of different fuel consumption impact factors.The model provides a theoretical analysis basis for the research of multimode energy management strategy of the HHMHS.Fourthly,an improved global optimization algorithm for the HHMHS is proposed to ensure the optimality of multimode energy management strategy.Considering the operating characteristics of the energy release limitation of accumulator at high-speed driving conditions and the "dimension disaster" problem of global optimization algorithm,this paper designs the equivalent fuel consumption factor calculation method based on vehicle speed-accumulator state of charge(SOC)and the improved dimension reduction global optimization algorithm based on the working characteristics of the HHMHS,respectively.And the improved algorithm can achieve high calculation efficiency without affecting the accuracy of the optimization results.Fifthly,a hierarchical-control-based multimode energy management strategy is proposed.In the driving condition adaptation layer,the mapping set between different working conditions,vehicle states and target operating mode is established by using fuzzy logic.And the matching problem between vehicle driving conditions and system operating mode is resolved.In the optimal control layer,optimal control rule extraction and linear quadratic regulator design are completed,according to the in-depth analysis of the global optimization results.And an optimal control layer control method is developed to obtain an approximate optimal online control rule,which is based on fixed threshold and tracking control of target SOC.Finally,the driving force coordination control strategy based on model predictive control and the nonlinear controller based on Lyapunov stability principle are designed.And then a nonlinear dynamic coordination integrated controller with good implementation effect is obtained to solve the coupling control problem of coordinated distribution of driving forces and essential non-linearity of the HHMHS,and to ensure the dynamic control quality in system operating process.In order to verify the proposed multimode energy management and non-linear dynamic coordination control strategy,this paper built hardware-in-the-loop test platform for the HHMHS,using dSPACE/Simulator and TTC200 rapid prototyping controller,and testing verification of integrated control strategy is carried out.The effectiveness and real-time performance of the proposed joint observation algorithm for driving conditions and system states,multimode energy management strategy and non-linear dynamic coordination control strategy are verified under the CBDTRUCK cycle condition,actual road test condition and nominal simulation condition of heavy commercial vehicle,respectively.The comprehensive improvement of fuel economy,adaptability of driving conditions,dynamic performance,passability and dynamic control quality are realized.