Study On Performance Of Phosphoric Acid Fuel Cell And Two-stage Thermoelectric Composite System

With the rapid development of the economy,the environmental pollution problem caused by the use of traditional fossil fuels is becoming increasingly severe.Looking for new renewable energy systems that can improve energy conversion efficiency and reduce harmful gas emissions is gaining more and more attention.Fuel cells have become one of the most attractive renewable energy technologies due to their high conversion efficiency and low environmental impact.Among various fuel cells,phosphoric acid fuel cell(PAFC)is regarded as one of the most well-established hydrogen-oxygen fuel cell technologies due to its relatively low-cost electrolyte and high durability.The thermoelectric generator can directly convert heat into ecletricity through the Seebeck effect.It has the advantages of small volume,quiet,no pollution,flexibility to various heat sources,etc.and has a good development prospect in waste heat recovery technology.The model of a hybrid power generation system that utilizes the waste heat of PAFC to drive a two-stage semiconductor thermoelectric generator(TTEG)is established,where the main irreversible loss in the system is considered comprehensively.The optimal regions of the hybrid system and the optimum matching conditions of the load resistances are determined.The best match condition for the resistor.Finally,the PAFC-TTEG hybrid system was optimized by multi-objective genetic algorithm NSGA-II.The specific research content is arranged as follows:The first chapter summarizes the background of this paper,introduces the development history and research status of phosphoric acid fuel cell,thermoelectric generator and multi-objective genetic algorithm.Finally,the main research contents of this paper are introduced.The second chapter establishes the thermodynamic theoretical model and mathematical model of serial TTEG and parallel TTEG,and introduces the working principle of TTEG.The first law of thermodynamics is used to derive the expression of output power,efficiency,entropy generation rate and ecological coefficient of performance(ECOP)of serial and parallel TTEG.The effects of the configuration for top stage and bottom stage thermoelectric component,hot and cold end temperature difference,and dimensionless figure of merit on the performance of two stypes TTEG were discussed.The third chapter establishes the mathematical model of PAFC running under steady state.The PAFC-series TTEG and PAFC-parallel TTEG composite power generation system models are established based on the optimized series TTEG and parallel TTEG in Chapter 2,respectively,where the overpotential losses in electrochemical reaction of PAFC,the regenerative losses,the heat leak and the main irreversibilities losses in TTEG are taken into account.General expressions of power output density,efficiency and entropy generation rate of the PAFC,TTEG and hybrid system are derived.The fundamental relationship between the operating current density of PAFC and TTEG is obtained.The optimal regions of the hybrid system are determined.The optimum match condition for the load resistances is given.The fourth chapter uses the multi-objective evolutionary algorithms based on NSGA-II to optimize the PAFC-series TTEG hybrid system that established in chapter 3.There the operating current density,operating temperature,operating pressure of PAFC and the non-dimensional figure of merit of thermoelectric material are selected as the decision variable,and the output power,efficiency and entropy generation rate of the hybrid system are taken as the objective function,and the optimization is operated in the parameter range discussed in chapter 3.Then,using three different decision methods to select the Pareto frontier of the optimization and determine the optimal solution.Finally,a comparative analysis of different optimization schemes was carried out.The fifth chapter summarizes the main contents and related conclusions of this paper,and puts forward some suggestions and prospects for the shortcomings of the current research.