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Parameter Estimation and Command Modification for Longitudinal Control of Heavy Vehicles

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  • Bae, Hong S.
  • Gerdes, J. Christian

Abstract

Commercial heavy vehicles, unlike passenger vehicles, display huge variation in parameters such as vehicle mass. Coupled with lower actuation authorities (engine and brake capabilities), these variations can induce actuator saturation even in moderately demanding maneuvers, presenting challenge to the task of maintaining string stability in a platoon formation of heavy trucks. A new control scheme is proposed to put on-line bounds, or artificial saturation, on command signals via parameter estimation such that all members in a platoon can follow the reference commands without saturating actuators, thereby, maintaining string stability. This work also demonstrates two methods for obtaining an estimate of road grade using a Global Positioning System (GPS) system on a ground vehicle. In the first method, two antennae are used to directly measure the attitude of the vehicle in the pitch plane; in the second method, the ratio of vertical to horizontal velocity at a single antenna is used to estimate road grade. The resulting grade measurements are then used together with engine torque information to produce estimates of mass, rolling resistance and aerodynamic drag from a simple longitudinal force balance. The resulting mass estimation consistently converged to within 2% of the true vehicle mass. Keywords: Parameter estimation, GPS, pitch, road grade, command modification, automated highways, automated commercial heavy vehicles, actuator saturation, string stability.

Suggested Citation

  • Bae, Hong S. & Gerdes, J. Christian, 2003. "Parameter Estimation and Command Modification for Longitudinal Control of Heavy Vehicles," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt6s35h1ch, Institute of Transportation Studies, UC Berkeley.
  • Handle: RePEc:cdl:itsrrp:qt6s35h1ch
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    Cited by:

    1. J. Piao & M. McDonald, 2008. "Advanced Driver Assistance Systems from Autonomous to Cooperative Approach," Transport Reviews, Taylor & Francis Journals, vol. 28(5), pages 659-684, February.
    2. Nan Lin & Changfu Zong & Shuming Shi, 2018. "The Method of Mass Estimation Considering System Error in Vehicle Longitudinal Dynamics," Energies, MDPI, vol. 12(1), pages 1-15, December.

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