Intelligent optimization on test bench of electric power steering device in automobile

Automotive steering system is used to change the direction and keep vehicles traveling straight. Electric power steering system (EPS) can improve vehicle handling performance and economy, has become one of hot spots on research and development in modern automobile steering system. Worm gears are important components of the electric power steering system; its transmission efficiency shall affect directly transmission efficiency and reset ability of the electric power steering system. Therefore, it is very important to adopt optimization methods to design the electric power steering systems. The fuzzy optimization model is established to design EPS. The method of second-class comprehensive evaluation was used by the optimal level cut set, thus the fuzzy optimization is transformed into the conventional optimization. This drawback of the genetic algorithm can be overcome by combining it with local gradient-based algorithms, which are known for their faster convergence. This hybrid approach improves the efficiency of the algorithm and also avoids the need to specify a good initial point for the derivative-based methods. A hybrid algorithm combining the genetic algorithm and local algorithm are developed in this paper, and the genetic algorithm can be combined with fuzzy logic to efficiently find a more accurate solution.