Study On The Real-time Optimization Energy Management Strategy Of Hybrid Electric Vehicles

In the background of increasing problems of energy and environment,the hybrid electric vehicle(HEV),as a new energy vehicle with the broad prospect of industrialization,has the advantages of both of conventional and electric vehicles and can effectively relieve the pressure of energy and environment brought by automobile industry.However,the introduction of battery in HEV generates a new control degree of freedom,which leads to the more complex coordination control of power sources.Therefore,there is extremely important practical significance to study the energy management problem of HEV.For the problem that existing energy management strategies can not consider the fuel economy and real-time performance simultaneously,the linear quadratic optimal control theory is applied to the energy management problem of HEV for the first time,aiming to propose the real-time power split strategies,which are independent of future driving cycle and have high fuel economy similar to the global optimal control based on Pontryagin's minimum principle(PMP).The main work of this dissertation is summarized as follows:Firstly,the regulation mechanism of optimal operating point of an engine is discussed combined with the power coupling HEV,then the control variables are reduced from the torque and speed to power.The linear vehicle model(assuming that the road slope is zero)and battery-motor model are established with the HEV in Advanced vehicle simulator(ADVISOR)as a prototype,which provides the foundation for the application of linear quadratic optimal control theory.Secondly,the pedal signal is considered as the vehicle speed command,based on which,the linear model of HEV is established with the square of vehicle speed and residual energy of battery as state variables and the engine power and motor power as control variables.Then the quadratic performance indexes are constructed to indirectly reduce fuel consumption from the perspective of averaging the engine power and motor power to smooth the engine power.Using linear quadratic state regulator and output tracker theory,we derive the control laws respectively consisted of state feedback with constant gain matrix and consisted of both of state feedback and command feedforward with constant gain matrixes.In other words,current control variables are only related to current states and commands,and independent of future driving cycle.To overcome the influence of road slope on above two strategies,the integral of deviation of original system states from their desired values is considered as the extended state to reestablish the extended model of HEV and corresponding quadratic performance index.The control law derived based on linear quadratic regulator theory contains not only the state feedback of original system,but also the integral action of state deviation.The comparative simulations demonstrate that above three proposed strategies have good adaptability to driving cycles and initial values of battery state of charge(SOC),and achieve the fuel economy very close to the PMP-based strategy.Additionally,the extended regulator strategy has better adaptability to the road slope.Finally,the pedal signal is considered as the torque command.And the linear model of HEV is established with the residual energy of battery as the state variable and the motor power as the control variable.The corresponding performance indexes are designed respectively from the perspectives of indirectly and directly saving fuel.The former aims at restricting large fluctuations of engine power,while the latter directly takes the fuel consumption as the optimization goal by the approximate quadratic function relation between the fuel consumption rate and engine power.Based on linear quadratic tracker theory,the control law can be derived,which is consisted of state feedback and command feedforward with constant gain matrixes,and independent of future driving cycle.The comparative simulations validate that above proposed strategies have significant fuel-saving effect and good adaptability to driving cycles and initial values of battery SOC.