Research On Modeling And Energy Optimization Of Exhaust Thermoelectric Generation New Electrical System For Heavy-duty Vehicles

It is suitable for recovering and utilizing by thermoelectric generation technology due to the fast flow rate and mass heat energy of heavy-duty vehicle diesel engine exhaust gas,and large space.The performance of the on-board thermoelectric generation device covers the entire chain optimization from thermoelectric modules to thermoelectric generator,and to automotive application.Therefore,according to the application requirements of heavy-duty vehicle and the multi-source nonlinear coupling characteristics of the on-board exhaust thermoelectric generation new electrical system,the power distribution of multi-energy sources is determined by the energy flow operating mode,which reduces the fuel consumption cost of the system,thereby improving its fuel economy.In this paper,exhaust thermoelectric generation-based new electrical system of heavy-duty vehicle is taken as the research object,and researches on system modeling and energy optimization are carried out.The main research contents and results are as follows:Thermoelectric generator,localized air conditioner,and existing heavy-duty vehicle electrical system are integrated to build the mixed logic dynamic(MLD)model of an on-board exhaust thermoelectric generation-based new electrical system.Firstly,system component models are established,including that variable physical properties' thermal resistance network model of thermoelectric generator is built based on the finite volume method and recursive least square method,and the performance of on-board generator,(state of charge)SOC change rate of lead-acid battery pack,DC/DC converter efficiency,power demand characteristics of localized air conditioners and original automotive appliances are analyzed.Secondly,the system energy flow is analyzed under six working modes including diesel engine starts,low speed and low load,low speed and high load,high speed and high load,high speed and low load,and short-term flameout.Finally,introducing the MLD modeling method,a system-integrated MLD model consisting of state equations and constraints is established.For the on-board thermoelectric generator consisting of a number of thermoelectric modules,the correlation between the thermal topology of thermoelectric modules and energy efficiency,and optimization algorithms are studied.Independent test factors(number and distribution of thermoelectric modules)are tested according to the Plackett-Burman experimental design.The significance of test factors are obtained through regression analysis,and important factors are selected.The response surface form of important factors is established based on the central composite rotation design.Non-dominated sorting genetic algorithm which selects energy efficiency(the maximum output power and thermoelectric conversion efficiency)of the thermoelectric generator as performance indicators is proposed.The Pareto optimal solution is ranked by the technique for order preference by similarity to ideal solution to obtain a set of optimal solutions.Simulation results show that compared with the initial design,the maximum output power and thermoelectric conversion efficiency of the optimized thermoelectric generator are significantly improved.To make sure that on-board thermoelectric generator operates the maximum output power,the on-board thermoelectric generation DC/DC converter-based maximum power tracking modeling and control scheme is proposed.Dynamic small signal analysis of the nonlinear Buck circuit is run based on the state space averaging method,and linear AC small signal model of Buck circuit is established.The reference voltage at the maximum power of the thermoelectric generator is calculated by the adaptive variable step artificial neural network(ANN)method.Meanwhile,a fuzzy PID controller is proposed to correct the PID parameters to improve the dynamic response and steady state performance of the voltage closed loop.The proposed maximum power tracking control scheme is validated in Matlab/Simulink simulation environment through the exhaust gas inlet temperature and mass flow variation.Aiming at the on-board exhaust thermoelectric generation-based new electrical system,SOC reference of lead-acid battery pack is calculated by dynamic programming algorithm.The theoretical basis and operation process of model predictive control are elaborated.The explicit model predictive control strategy is adopted to solve the optimal solution sequence of on-board generator torque,and the control module in the ADVISOR simulation platform is built based on the control sequence.Simulation results show that the model predictive control strategy based on MLD model can effectively improve the fuel economy of the on-board exhaust thermoelectric generation-based new electrical system under the urban dynamometer driving schedule(UDDS)and new European driving cycle(NEDC).Heavy-duty vehicle-based thermoelectric generation experimental bench is established,then bench tests and road tests are carried out.The output performance of the thermoelectric generation device is tested,and the effectiveness of thermal topology optimization structure of thermoelectric module group,and the maximum power tracking control scheme is verified.In summary,key issues such as MLD modeling of on-board exhaust thermoelectric generation-based new electrical system,correlation analysis and optimization between thermoelectric module thermal topology and energy efficiency,maximum power tracking for DC/DC converter of thermoelectric generation,and energy management for thermoelectric generation-based new electrical system have been studied to improve the electrical performance of thermoelectric generator and the fuel economy of on-board exhaust thermoelectric generation-based new electrical system.