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Model Predictive Current Control of a Slow Battery Charger for Electric Mobility Applications

Part of the Lecture Notes in Electrical Engineering book series (LNEE,volume 402)

Abstract

This paper presents a model predictive current control applied to a slow electric vehicle (EV) battery charger. Taking into account the similarities between the power converters inside the EV, it is possible to combine the battery charger and the motor driver in a single integrated converter, thus reducing the weight and volume of the proposed solution, and also contributing to reduce the final price of the EV. Due to the bidirectional power flow capability of the integrated power converter, when working as a slow EV battery charger it can operate in grid-to-vehicle (G2V) mode and in vehicle-to-grid (V2G) mode, contributing to make EVs an important assets in the future smart grids. The integrated power converter working as battery charger operates with sinusoidal current and unitary power factor, contributing to improve the power quality of the electrical grid. This paper provides simulation and experimental results that validate the model predictive control algorithm applied to the proposed integrated power converter working as slow EV battery charger.

Keywords

  • Electric vehicles
  • Slow battery charger
  • Model predictive current control
  • G2V—Grid-to-Vehicle
  • V2G—Vehicle-to-Grid

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  • DOI: 10.1007/978-3-319-43671-5_54
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Acknowledgments

This work has been supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT – Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2013. Mr. Delfim Pedrosa was supported by the doctoral scholarship SFRH/BD/86628/2012 granted by the FCT agency.

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Pedrosa, D., Gomes, R., Monteiro, V., Afonso, J.A., Afonso, J.L. (2017). Model Predictive Current Control of a Slow Battery Charger for Electric Mobility Applications. In: Garrido, P., Soares, F., Moreira, A. (eds) CONTROLO 2016. Lecture Notes in Electrical Engineering, vol 402. Springer, Cham. https://doi.org/10.1007/978-3-319-43671-5_54

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  • DOI: https://doi.org/10.1007/978-3-319-43671-5_54

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