Application and Research of Particle Swarm optimization in window anti-pinch test system

There are many redundancies in the manually-written power window anti-pinch algorithm test cases, and the anti-pinch algorithm cannot be fully covered, and the test purpose is not achieved. This paper analyzes the window anti-pinch control algorithm, uses the particle swarm optimization algorithm(PSO) to optimize the test path, introduces the weight array and pile insertion technology to speed up the iterative update of the algorithm, uses the branch function superposition method to count the path coverage, finds the optimal solution is the end of the algorithm, then outputs the test case set. Through the functional test of the window regulator Electronic Control Unit(ECU) product of a certain vehicle, the efficiency of using PSO to generate test cases is 16.7% higher than that of random algorithm(RA), which basically realizes the full coverage of anti-pinch algorithm and ensures the reliability of the anti-pinch algorithm.