为了使学科赛事的实践经验能与更多人分享,对全国大学生“飞思卡尔”智能车竞赛中常见的三类问题(控制算法的选择、车模机械改装、电磁传感器布局)进行了研究,通过理论计算、模拟仿真以及借鉴现场调试经验对这三类常见问题进行了剖析,并给出了可行的解决方案.智能车的角度控制和速度控制分别采用PID控制算法和模糊控制算法,同时在恶劣条件下用模糊控制算法对PID控制算法进行补充,达到提高系统鲁棒性的目的；给出了如何合理地调整车模前束角和重心这两个重要机械参数的方法,突破当前智能车速度的瓶颈；提出了一种双水平线圈的改进方案,节约成本的同时增强了电磁传感器的灵敏度,并且通过增加竖直方向的线圈提高了智能车的前瞻性.%Three types of the common problems ( control algorithms, mechanical modifications of the car models, and electromagnetic sensors layout) in National Undergraduate "Freescale" smart car competition were studied in this paper. Through theoretical calculation,simulation and the experience of practical debugging,a more comprehensive analysis was conducted for those three types of problems,and some possible solutions were given. The P1D control algorithm and the fuzzy control algorithm were used respectively to angle control and speed control of the smart car,while operating in harsh conditions,the fuzzy control algorithm was used to supplement the PID control algorithm,which could also improve the robustness of the system. Some reasonable methods in order to adjust the two important mechanical parameters (the toe and the center of gravity)of the smart car are given in order to increase the current speed. An improving solution for the bi-level coil was proposed which not only saved cost, but also enhanced the sensitivity of magnetic sensors, and by increasing the vertical direction coil,increased the forward-looking of the smart car.
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