To better qualify various uncertainties in design and manufacturing, as well as to understand the time-varying degradation process, a novel method of quality and reliable design and optimization for high-power DC actuators was developed in this study that considered relevant uncertainties in design, manufacturing parameters, and the degradation process. Orthogonal transformation was used to normalize heterogeneous uncertainties and the results were quantitatively described by the hyperellipsoid set model. On the basis of the uncertainty quantitative relationship, a fast substitution model was developed for high-power DC actuators with permanent magnet output characteristics of strong non-linearity and insufficient accuracy. The response surface method was used to derive the basis function, and the error between the practical measured values and the calculation values was modified by the radial basis function model. Afterwards, a life cycle global sensitivity analysis method was put forward to determine the design parameters when parameter degradation existed during the life cycle of high-power DC actuators. Then, an optimization model was established considering parameter uncertainties and reliability constraints, and the particle swarm algorithm was used to obtain the solution. Finally, the effectiveness of the proposed method was verified by a case study of high-power DC actuators in electric vehicles.
A Novel Method for Technology Forecasting and Developing R&D Strategy of Building Integrated Photovoltaic Technology Industry