关键词: 油门控制；负载工况；驾驶风格；商用车

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