A comparative study between causal and non-causal algorithms for the energy management of hybrid storage systems

• Type: Article in International Conference Proceedings Book
• Date: 2013

Authors

Pinto, C (Author) Other; De Castro, R (Author) Other; Rui Esteves Araújo (Author) FEUP

Conference proceedings International

Title: 2013 15th European Conference on Power Electronics and Applications, EPE 2013

2013 15th European Conference on Power Electronics and Applications, EPE 2013

Lille, 2 September 2013 through 6 September 2013

Indexing

Scopus - 3 Citations

Other information

Authenticus ID: P-008-JJT

DOI: 10.1109/epe.2013.6634702

Abstract (EN): This paper presents a comparative study between two non-causal algorithms for the energy management problem of electric vehicles, endowed with batteries and supercapacitors(SCs). Toward that goal, an optimization-based energy problem is formulated, which targets the minimization of the source's energy losses throughout a given driving cycle. This problem is solved, firstly, with the help of a fast (but locally optimal) non-linear programming solver; and, secondly, with a slow, but globally optimal, dynamic programming (DP) approach. Simulation results will demonstrate that, despite the different theoretical properties associated with these two solver approaches, both generate similar solutions. In the second part of the work, we will develop a filter-based energy management algorithm, i.e., employ batteries to provide the low-frequency content of the power demand, while SCs cover the high-frequency demand. Our approach builds on the idea of adapting the filter's time constant throughout the vehicle's journey, using, for that purpose, a fuzzy logic algorithm and the information of the state of the vehicle. In comparison with the traditional fixed time-constant approach, the simulation results show that under some conditions the adaptive time-constant algorithm has the potential to reduce the energy losses of the sources by up to 62%. © 2013 IEEE.

Language: English

Type (Professor's evaluation): Scientific