Abstract: With the increasing demand for intelligence and energy efficiency in commercial vehicles, this paper proposes a throttle control method based on the recognition of load conditions and driving styles. The method processes vehicle operation data using the K-Means clustering algorithm to identify three load conditions (high, medium, low) and classifies driving styles into aggressive, normal, and calm categories based on features such as vehicle speed, throttle opening, and braking. Accordingly, the throttle characteristic curve and torque output coefficient are dynamically adjusted to balance power performance and fuel economy. Real vehicle tests demonstrate that the strategy can adaptively adjust control parameters according to real-time conditions and driving styles, significantly improving fuel economy while ensuring power performance and driving smoothness. This study provides a valuable reference for the development of intelligent throttle control strategies in commercial vehicles.

Key words: throttle control; load condition; driving style; commercial vehicle

摘要： 随着商用车智能化与节能化需求的提升，文章提出一种基于负载工况与驾驶风格识别的 油门控制方法。该方法通过 K-Means 聚类算法对车辆运行数据进行处理，识别出高、中、低 三种负载工况，并结合车速、油门开度、制动等特征将驾驶风格分为激烈、一般、平静三类。 在此基础上，动态调整油门特性曲线与扭矩输出系数，以实现动力性与经济性的平衡。实车 测试表明，该策略能根据实时工况与驾驶风格自适应调整控制参数，显著提升燃油经济性， 同时保证车辆动力性与驾驶平顺性，为商用车智能化油门控制提供了有效参考。

关键词: 油门控制；负载工况；驾驶风格；商用车