Search Results

This paper presents a novel powertrain control system specifically designed for longitudinal motion-control applications of an automated-manual-transmission vehicle, whereby the clutch and throttle modulation and gear change are highly coordinated such that the vehicle can precisely track the target acceleration or deceleration command even during an upshift or a downshift. An observer-free method for estimation of the engine’s operating point under various working condition is developed to compensate for limited sensing and enable effective feed-forward control of the engine torque and the clutch pressure. With minor modifications of the coordination strategies in the existing powertrain control system, the proposed control system can prevent stalling the engine from a standing start and achieve smoother shifting and faster dynamic response of the powertrain system, where non-smooth actuator nonlinearities are addressed explicitly, robustly, and efficiently.

This paper presents a HiL test bench specifically designed for closed-loop testing of the monocular-vision based ADAS sensors, whereby the animated pictures of the virtual scene is calibrated and projected onto a 120-degree circular screen, such that the camera sensor installed has the same vision as the observation of the real-world scene. A high-fidelity AEBs model is established and deployed in the real-time target of the HiL system, making intervention decisions based on the instance-level detection information transmitted from the physical sensor. By referring to the 2018 edition of the C-NCAP testing protocol, the HiL tests of the rear-end collision scenarios is performed to investigate the performance and characteristics of the longitudinal-motion sensing of the sensor sample under test.