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Enhancement of Yaw and Roll Stability for Trucks by Estimating Payload Conditions

Journal Article
2012-01-0230
ISSN: 1946-391X, e-ISSN: 1946-3928
Published April 16, 2012 by SAE International in United States
Enhancement of Yaw and Roll Stability for Trucks by Estimating Payload Conditions
Citation: Koto, H., Kato, T., Nitta, C., Suzuki, K. et al., "Enhancement of Yaw and Roll Stability for Trucks by Estimating Payload Conditions," SAE Int. J. Commer. Veh. 5(1):94-100, 2012, https://doi.org/10.4271/2012-01-0230.
Language: English

Abstract:

Electronic stability control (ESC) is being incorporated as a standard feature in almost all passenger cars since it is highly effective in reducing road accidents. Moreover, many commercial vehicles can be equipped with ESC, which includes roll stability control. ESC determines vehicle stability on the basis of the driver's operation, vehicle behavior, and preset control parameters. When the vehicle stability is likely to be lost, control intervenes to stabilize the vehicle. The characteristics of commercial vehicles affect the ESC parameters and vary significantly with the payload (e.g., weight and height of the cargo and the loading state). Therefore, the control parameters need to be adjusted according to the loading conditions to enhance vehicle stability and avoid unnecessary control intervention.
We have developed an ESC that improves the yaw and roll stability of trucks. For this development, accurate evaluation of the payload states is important. The payload states, in turn, are determined by estimating the vehicle mass accurately. Essentially, the vehicle mass is estimated on the basis of the driving force and the longitudinal acceleration when a vehicle is accelerating. The driving force is calculated from the engine speed and the throttle position, while the longitudinal acceleration is detected by sensors. However, the measured driving force and longitudinal acceleration include errors attributable to the aerodynamic drag of the vehicle body, rolling resistance of the tires, inertia force and friction loss of the power train, and zero drift of the sensors. An algorithm for estimating the vehicle mass has been developed to compensate for these errors. In this algorithm, the state variables when the gearshift is in the neutral position (i.e., when the vehicle is coasting) and in another position (i.e., when the vehicle is accelerating) are compared in order to nullify the errors. In this paper, we describe a vehicle mass estimation algorithm that adjusts the control parameters according to the payload conditions and discuss vehicle tests that demonstrate the effectiveness of ESC based on this estimation.