Performance Analysis And Optimization Of Space Nuclear Brayton Cycle System

With the further development of deep space exploration in the future,space nuclear power,compared with chemical energy and solar power,has obvious advantages of high power,high efficiency and long life,and will become the space power system with the greatest development potential.Space thermoelectric conversion technology is usually divided into static and dynamic system.At present,the research focus is gradually turning to dynamic conversion technology which is more efficient and reliable.In the dynamic thermoelectric conversion technology,the Brayton cycle,Stirling cycle and Rankine cycle thermoelectric conversion technology are mainly used.This article mainly aims at Brayton cycle system,which is mature and widely used.Kilowatt ideal regenerative Brayton cycle model and MW supercritical carbon dioxide（SCO₂）space compression Brayton cycle model are established,characteristics of these two systems are analyzed,and then the multi-objective optimization is made with genetic algorithm and the Pareto optimal boundary curve is obtained.In the ideal kilo-regenerative Brayton cycle,the submerged subcritical space reactor is used as prototype to establish a model,and the influences of variable regenerative heat,variable working medium（Helium and Carbon Dioxide）,and variable external conditions on cycle efficiency and cycle work are explored.The optimal parameters are the cycle efficiency is 0.319,the circulation work are 1.2512×10⁶W,the radiator temperature T₁ is400.25 K,the reactor outlet temperature T₃ is 1000 K,the regenerator effectiveness is 0.5and the cycle pressure ratio is 2.In the SCO₂ MW-recompression Brayton cycle,the PR equation is used to modify the physical properties of the actual CO₂ in the critical state.Considering the particularity of space environment,heat exchanger thermal conductivity model and levelized energy cost model（LEC）are established.The characteristics of the system are analyzed under different operating conditions.On the basis,the regression relationship amount the cycle thermal efficiency,exergy efficiency,regenerator thermal conductivity,the radiator area,LEC and compressor inlet temperature,turbine inlet temperature,the compressor inlet pressure,the circulation ratio and amount of shunt are obtained by response surface methodology（RSM）.Then,the fast non-dominant ranking algorithm with elite strategy（NSGA-II）was used to optimize the system in groups of three objectives,and Pareto optimal boundary curve and optimal solution set under different objective functions were obtained.Taking thermodynamic performance and economic performance into consideration,with the cycle thermal efficiency,the radiator area and LEC as optimization target,finally A set of optimized solution is obtained that when T₁=325K,T₅=880K,π=3.3,P=7.44MPa,x=0.286,the cycle thermal efficiency isη=0.264,the radiator area A=1463.48m²,LEC=0.0417$/kWh.