Abstract: In order to further improve the safety of pneumatic braking system under complex road surface, the braking performance of agricultural fourwheel tractor was studied. Aiming at the shortage of convergence speed and accuracy of standard particle swarm optimization (PSO), an improved particle swarm optimization (IPSO) algorithm was proposed. The results of four test functions of the two algorithms showed that IPSO had faster convergence speed and higher accuracy. Through the test and system identification method, the pneumatic braking system model was identified, and based on this, a simulation model of ABS braking performance of agricultural fourwheel tractor with pneumatic braking system was built considering the drivers operation behavior, so as to restore the real braking process. The braking performance of IPSO-PID control algorithm under special road surface was simulated and analyzed. The results showed that the braking distance and braking time of ABS controlled by IPSO-PID were 15.12 m and 219 s, respectively, which were 8.25% and 10.61% shorter than those without control. In the case of staggered road braking, the braking distance and braking time of ABS controlled by IPSO-PID were 15.47 m and 2.29 s, which were 781% and 10.55% shorter than those without control, respectively. 

Key words: tractor, braking performance, pneumatic brake, improved particle swarm optimization algorithm

摘要： 为进一步提高气压制动系统农用四轮拖拉机在复杂路面下的行车安全性，对其制动性能进行研究。针对标准粒子群算法(PSO)收敛速度和精度的不足，提出一种改进粒子群算法(IPSO)，对比二者的四个测试函数运行结果表明：IPSO收敛速度更快，精度更高。通过试验结合系统辨识的方法，对气压制动系统模型进行辨识，并基于此搭建考虑驾驶员操作行为在内的气压制动系统农用四轮拖拉机ABS制动性能仿真模型，以此还原真实的制动过程。对IPSO-PID控制算法的特殊路面下制动性能进行仿真分析，结果表明：对接路面制动时，采用IPSO-PID控制ABS制动距离为1512m，制动时间为219s，分别比无控制时缩短825%和1061%；交错路面制动时，采用IPSO-PID控制ABS制动距离为1547m，制动时间为229s，分别比无控制时缩短781%和1055%。

关键词: 拖拉机, 制动性能, 气压制动, 改进粒子群算法