In order to improve the fan noise, the multi-objective optimization algorithm was implemented to optimize the fan blade structure. Firstly, the theoretical model with the noise, flow rate and power of fan as the objectives was established and verified; then, the global sensitivity analysis method based on sobol’ method was used to obtain the contributions of each parameter to the performance objectives of the fan by taking the fan blade angle and chord length as the analysis parameters; finally, the sensitive parameters are selected to obtain the best noise-oriented comprehensive performance of the fan by the genetic algorithm. The result shows that the noise is reduced by 3.1dB, the flow rate is increased by 7.7% and the power is reduced by 7.9% after optimizing fan blade structure, and the overall performance of the fan is significantly improved.
Electric power steering (EPS) system is becoming the primary source of Electric Vehicle (EV) noise due to absence of classic power train. The rattle noise produced by EPS, which is easily discernible when driving. Since the conventional subjective evaluation approach makes it difficult to identify the source, it is required to establish an objective way to solve such an issue. In this paper, the principle of multiple coherence method is first addressed analytically, and then is employed to analyze the vibration signal acquisition from EPS different points, meanwhile, combine with in-car sound signal, to accurately identify the specific location.
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