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Model Predictive Control Based Energy Management Algorithm for a Hybrid Excavator

Thuring, Patrik (2008) In MSc Theses
Department of Automatic Control
Abstract
The Volvo Group has an ambitious plan to efficiencies its construction equipment vehicles with an introduction of a hybrid engine. This Master thesis is based on, as a first approach, to control the energy split in a hybrid construction equipment vehicle (HCEV) with the control strategy Model Predictive Control (MPC). The work is divided into two main parts, where the first one is to create a piece-wise affine system (PWA) of the nonlinear plant and secondly to define the control strategy. Multiple linear models are created from the different mathematical descriptions with the Taylor expansion and then divided in space with polytopes to represent the hybrid dynamics properly. After that, the MPC strategy is to be created and this is done... (More)
The Volvo Group has an ambitious plan to efficiencies its construction equipment vehicles with an introduction of a hybrid engine. This Master thesis is based on, as a first approach, to control the energy split in a hybrid construction equipment vehicle (HCEV) with the control strategy Model Predictive Control (MPC). The work is divided into two main parts, where the first one is to create a piece-wise affine system (PWA) of the nonlinear plant and secondly to define the control strategy. Multiple linear models are created from the different mathematical descriptions with the Taylor expansion and then divided in space with polytopes to represent the hybrid dynamics properly. After that, the MPC strategy is to be created and this is done by defining a cost function, where selected variables should follow some trajectory. At each sample, the MPC controller should compute an optimal control signal during the prediction and control horizon to minimize the fuel consumption, make the internal combustion engine run at a favourable rotational speed and save the durability on the battery. The control problem is simulated in Simulink with a pre-defined driving cycle, as can be seen as an artificial user for the HCEV, which generates a power demand that needs to be satisfied (Less)
Please use this url to cite or link to this publication:
author
Thuring, Patrik
supervisor
organization
year
type
H3 - Professional qualifications (4 Years - )
subject
publication/series
MSc Theses
report number
TFRT-5825
ISSN
0280-5316
language
English
id
8847649
date added to LUP
2016-03-17 10:24:43
date last changed
2016-03-17 10:24:43
@misc{8847649,
  abstract     = {The Volvo Group has an ambitious plan to efficiencies its construction equipment vehicles with an introduction of a hybrid engine. This Master thesis is based on, as a first approach, to control the energy split in a hybrid construction equipment vehicle (HCEV) with the control strategy Model Predictive Control (MPC). The work is divided into two main parts, where the first one is to create a piece-wise affine system (PWA) of the nonlinear plant and secondly to define the control strategy. Multiple linear models are created from the different mathematical descriptions with the Taylor expansion and then divided in space with polytopes to represent the hybrid dynamics properly. After that, the MPC strategy is to be created and this is done by defining a cost function, where selected variables should follow some trajectory. At each sample, the MPC controller should compute an optimal control signal during the prediction and control horizon to minimize the fuel consumption, make the internal combustion engine run at a favourable rotational speed and save the durability on the battery. The control problem is simulated in Simulink with a pre-defined driving cycle, as can be seen as an artificial user for the HCEV, which generates a power demand that needs to be satisfied},
  author       = {Thuring, Patrik},
  issn         = {0280-5316},
  language     = {eng},
  note         = {Student Paper},
  series       = {MSc Theses},
  title        = {Model Predictive Control Based Energy Management Algorithm for a Hybrid Excavator},
  year         = {2008},
}