Development of a Novel Sensorless Longitudinal Road Gradient Estimation Method Based on Vehicle CAN Bus Data

The availability of road gradient information will have a big impact upon the quality of vehicle control. This paper presents a novel "sensorless" longitudinal road-gradient estimation method, which was developed in two steps starting from a benchmark system design. The gradient benchmark system consists of an inclinometer sensor and an acceleration-based error correction algorithm, which can be used to verify the accuracy of the road gradient obtained using a sensorless estimation method. The sensorless road-gradient estimation algorithm uses the vehicle data currently available on the vehicle controller area network (CAN) bus. The completed gradient estimation algorithm was successfully tested online in variable road conditions and different driving manners. The test results showed that the resulting longitudinal road-gradient estimation algorithm fulfilled the specified accuracy requirement, and provided a cost effective and reliable way for longitudinal road-gradient estimation in real time.