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contributor authorBoyle, Stephen
contributor authorStockar, Stephanie
date accessioned2022-05-08T09:02:24Z
date available2022-05-08T09:02:24Z
date copyright11/12/2021 12:00:00 AM
date issued2021
identifier issn0022-0434
identifier otherds_144_01_011103.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4284658
description abstractConnected and autonomous vehicles (CAVs) have the ability to use information obtained via vehicle-to-infrastructure (V2I), vehicle-to-vehicle (V2V) communication, and sensors to improve their fuel economy through predictive strategies, including velocity trajectory optimization and optimal traffic light arrival and departure. These powertrain control strategies operate on a slow timescale relative to the engine dynamics
description abstracthence, assume that the engine torque production is instantaneous. This assumption results in a torque command profile that may lead to engine dynamics constraint violation, actuator saturation, poor tracking performance, decreased efficiency, poor drivability, and increased emissions. To address this issue, a supplemental controller based on an iterative hierarchical model predictive control (MPC) is proposed in this paper. The constraint satisfaction is achieved through a novel two-way communication of the Lagrange multipliers. The proposed methodology is demonstrated on an autonomous diesel semitruck on two maneuvers. Compared to a traditional centralized approach, the proposed method achieves systematic constraints' satisfaction with negligible effect on fuel economy, less than 1%, and significantly improved computation time, more than ten times.
publisherThe American Society of Mechanical Engineers (ASME)
titleMulti Time-Scale Engine and Powertrain Control for Autonomous Vehicles Via Lagrange Multipliers
typeJournal Paper
journal volume144
journal issue1
journal titleJournal of Dynamic Systems, Measurement, and Control
identifier doi10.1115/1.4052766
journal fristpage11103-1
journal lastpage11103-12
page12
treeJournal of Dynamic Systems, Measurement, and Control:;2021:;volume( 144 ):;issue: 001
contenttypeFulltext


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