Stochastic Power Management Strategy for in-Wheel Motor Electric Vehicles
In this thesis, we propose a stochastic power management strategy for in-wheel motor electric vehicles (IWM-EVs) to optimize energy consumption and to increase driving range. The driving range for EVs is a critical issue since the battery is the only source of energy. Considering the unpredictable n...
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ndltd-LACETR-oai-collectionscanada.gc.ca-OWTU.10012-84452014-06-18T03:51:40Z Stochastic Power Management Strategy for in-Wheel Motor Electric Vehicles Jalalmaab, Mohammadmehdi Battery electric vehicle Power management systems In-wheel motor electric vehicle Stochastic programming Markov processes Dynamic programming In this thesis, we propose a stochastic power management strategy for in-wheel motor electric vehicles (IWM-EVs) to optimize energy consumption and to increase driving range. The driving range for EVs is a critical issue since the battery is the only source of energy. Considering the unpredictable nature of the driver’s power demand, a stochastic dynamic programing (SDP) control scheme is employed. The Policy Iteration Algorithm, one of the efficient SDP algorithms for infinite horizon problems, is used to calculate the optimal policies which are time-invariant and can be implemented directly in real-time application. Applying this control package to a high-fidelity model of an in-wheel motor electric vehicle developed in the Autonomie/Simulink environment results in considerable battery charge economy performance, while it is completely free to launch since it does not need further sensor and communication system. In addition, a skid avoidance algorithm is integrated to the power management strategy to maintain the wheels’ slip ratios within the desired values. Undesirable slip ratio causes poor brake and traction control performances and therefore should be avoided. The simulation results with the integrated power management and skid avoidance systems show that this system improves the braking performance while maintaining the power efficiency of the power management system. 2014-05-14T14:14:49Z 2014-05-14T14:14:49Z 2014-05-14 2014 Thesis or Dissertation http://hdl.handle.net/10012/8445 en |
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en |
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Battery electric vehicle Power management systems In-wheel motor electric vehicle Stochastic programming Markov processes Dynamic programming |
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Battery electric vehicle Power management systems In-wheel motor electric vehicle Stochastic programming Markov processes Dynamic programming Jalalmaab, Mohammadmehdi Stochastic Power Management Strategy for in-Wheel Motor Electric Vehicles |
description |
In this thesis, we propose a stochastic power management strategy for in-wheel motor electric vehicles (IWM-EVs) to optimize energy consumption and to increase driving range. The driving range for EVs is a critical issue since the battery is the only source of energy. Considering the unpredictable nature of the driver’s power demand, a stochastic dynamic programing (SDP) control scheme is employed. The Policy Iteration Algorithm, one of the efficient SDP algorithms for infinite horizon problems, is used to calculate the optimal policies which are time-invariant and can be implemented directly in real-time application. Applying this control package to a high-fidelity model of an in-wheel motor electric vehicle developed in the Autonomie/Simulink environment results in considerable battery charge economy performance, while it is completely free to launch since it does not need further sensor and communication system.
In addition, a skid avoidance algorithm is integrated to the power management strategy to maintain the wheels’ slip ratios within the desired values. Undesirable slip ratio causes poor brake and traction control performances and therefore should be avoided. The simulation results with the integrated power management and skid avoidance systems show that this system improves the braking performance while maintaining the power efficiency of the power management system. |
author |
Jalalmaab, Mohammadmehdi |
author_facet |
Jalalmaab, Mohammadmehdi |
author_sort |
Jalalmaab, Mohammadmehdi |
title |
Stochastic Power Management Strategy for in-Wheel Motor Electric Vehicles |
title_short |
Stochastic Power Management Strategy for in-Wheel Motor Electric Vehicles |
title_full |
Stochastic Power Management Strategy for in-Wheel Motor Electric Vehicles |
title_fullStr |
Stochastic Power Management Strategy for in-Wheel Motor Electric Vehicles |
title_full_unstemmed |
Stochastic Power Management Strategy for in-Wheel Motor Electric Vehicles |
title_sort |
stochastic power management strategy for in-wheel motor electric vehicles |
publishDate |
2014 |
url |
http://hdl.handle.net/10012/8445 |
work_keys_str_mv |
AT jalalmaabmohammadmehdi stochasticpowermanagementstrategyforinwheelmotorelectricvehicles |
_version_ |
1716670436202250240 |