Quantum Intelligent Optimization Algorithm And The Research On Its Application To Motor Optimization

Quantum computation is an emerging interdisciplinary science whichcombines information science and quantum mechanics. And quantumcomputation theory, represented by quantum algorithm, has great superiority andstrong vitality because it has a high degree of parallelism, the index level ofstorage capacity, and can speed up the classic heuristic algorithms, so it hasbecome the frontier research field for many relevant scholars around the word.The integration of traditional intelligent optimization algorithms and quantumcomputation theory changes iterative optimization method of traditionalintelligent optimization algorithms, improve iterative convergence rate andglobal search capability. Hence, the research on quantum intelligent optimizationalgorithm and its application to motor optimization has important theoretical andpractical significance. This dissertation mainly studied the continuous quantumant colony optimization、continuous quantum particle swarm optimization、continuous quantum immune clonal optimization、and the applications to motoroptimization, the specific content of the paper can be summarized as follows.1．Through integration of the quantum computation theory and the antcolony optimization, the continuous quantum ant colony optimization is proposed,the simulation results show that its convergence speed and approximation abilityare evidently superior to the ant colony optimization. The optimal design of a117kW level high speed permanent magnetic generator (HSPMG) cooingstructure is studied through thermal analysis and the quantum intelligentoptimization algorithm. The new cooling systems can make temperaturedistribute more evenly in HSPMG, and the influences of groove height and theaxial variation position on HSPMG temperature distributions are studied. Basedon the continuous quantum ant colony optimization, a mathematical optimizationmodel with dual objective functions and two dimensional variables for statorslots grooves optimal design is proposed, and a groove structure which could make both the windings axial largest temperature and the axial temperaturedifference to be the minimum ones is obtained by optimization algorithm. Theobtained conclusions may provide useful reference for the design and research ofcooling structure in HSPMG.2．Through integration of the quantum computation theory and the particleswarm optimization, continuous quantum particle swarm optimization isproposed, the simulation results show that the induction of quantum computationtheory can significantly improve the optimization efficiency of algorithm. Amathematical optimization model with multi-objective optimization for statorslots grooves optimal design is proposed based on the continuous quantum antcolony optimization, which could make the stator windings axial largesttemperature, the stator core axial largest temperature, the stator windings axialtemperature difference and the stator core axial temperature difference to be theminimum ones. According to the optimal solution of stator slots groovesdetermined by continuous quantum ant colony optimization, the motor axiallargest temperature and axial temperature difference in motor different positionsare decreased significantly, a new kind of optimization method is proposed forHSPMG cooling structure.3．Through integration of the quantum computation theory and the immuneclonal algorithm, the continuous quantum immune clonal optimization isproposed, and the simulation results show the optimization ability of continuousquantum immune clonal optimization is evidently superior to the immune clonalalgorithm. Multi-objective optimization with two dimensional variables forcooling structure in HSPMG is studied in depth. The stator windings axial largesttemperature, the stator core axial largest temperature, the rotor axial largesttemperature, the stator windings axial temperature difference, the rotor axialtemperature difference and the stator core axial temperature difference areselected as optimization goals, the stator slots grooves parameters dh and dloptimization are studied. The stator slots grooves optimal solution based on thecontinuous quantum immune clonal optimization make the motor axialtemperature distribution more uniform.