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Title: Non-linear model predictive control for energy-efficient motion strategy in a vehicle following scenario
Author: Ruta, M.
ISNI:       0000 0004 7968 8193
Awarding Body: Coventry University
Current Institution: Coventry University
Date of Award: 2017
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This thesis focuses on the design and implementation of the energy-efficient motion strategy inspired by Adaptive Cruise control (ACC). It exploits the ability to manage energy requirements using regenerative braking, freewheeling as well as efficient acceleration to determine an energy-efficient speed profile. A non-linear model of the vehicle equipped with the energy-efficient motion strategy was developed and validated against experimental data. The model incorporates a longitudinal vehicle dynamics as well as captures the powertrain losses contributing to the overall vehicle motion efficiency. A Non-linear Model Predictive Control (NMPC) strategy was subsequently developed to realise the energy-efficient motion concept. It required to formulation of the Optimal Control Problem (OCP) based on a cost function adopting three competing control objectives. Two objectives associated with energy-efficient vehicle motion were used to determine torque to be delivered by the electric machine of the following vehicle. The third objective was adopted to handle the speed difference between the preceding and following vehicle. The OCPO was complemented by a set of constraints to ensure a safe spacing gap between the vehicles and to incorporate physical limitations of the following vehicle. An effective implementation of the NMPC was realised through the use of open-source ACADO Toolkit package by which the OCP was implemented and subsequently solved using a real-time iteration scheme involving Sequential Quadratic programming (SQP). Simulation studies combining the validated non-linear following vehicle model and the NMPC were carried out for typical traffic scenarios. The impact of the trade-off between energy-efficient vehicle motion and accurate lead vehicle following was investigated by adjusting weightings of the cost function objectives. It was shown that appropriate selections of the weighting and handling of constraints enable to adjust the trade-off between energy consumption and accurate lead vehicle tracking. Although the duration of travel may be partially compromised, the resulting strategy offers a reduction of overall energy consumption for the considered traffic scenarios.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available