Particle Swarm Optimization of Fuzzy Logic Controller

Particle swarm optimization of fuzzy controller for hybrid energy storage system in electric vehicle

This submission presents the particle swarm optimization of the fuzzy logic controller (FLC) for a hybrid energy storage system (HESS) in an urban electric vehicle. The Sugeno-type fuzzy inference system has been applied to divide power between the battery and ultracapacitor energy storage systems, as well as to manage the amount of energy stored in ultracapacitors. The two output signals of the described fuzzy logic controller represent power for each energy storage system, and are the weighted sums of all inference rule outputs. The particle swarm optimization (PSO) has been proposed to determine the weights of rules.
In this submission simplified HESS model and simplified FLC is used. The fully developed HESS model is presented in [1, 2, 3]. Extended power management algorithm is presented in [4, 5]
Fuzzy inference system controls power of lithium-ion and ultracapacitor energy storage system in such a way that it does not affect the vehicle dynamic performance, and at the same time strives to minimize the instantaneous battery current. The fuzzy system tuning involving a determination of rule weights, has a significant impact on the controller performance. This process is complex and not evident, especially if the inference system has a lot of rules.

A detail description of the PSO will be presented at 18th European Conference on Power Electronics and Applications (http://www.epe2016.com/) in September.

[1] M. Michalczuk, L. M. Grzesiak and B. Ufnalski, "Experimental parameter identification of battery-ultracapacitor energy storage system," 2015 IEEE 24th International Symposium on Industrial Electronics (ISIE), Buzios, 2015, pp. 1260-1265.
http://dx.doi.org/10.1109/ISIE.2015.7281653
[2] M. Michalczuk, Li-ion battery model, http://www.mathworks.com/matlabcentral/fileexchange/48234
[3] M. Michalczuk, Ultracapacitor (Supercapacitor) model, http://www.mathworks.com/matlabcentral/fileexchange/51243
[4] Michalczuk, M., Ufnalski, B., Grzesiak, L. M. (2015). „Fuzzy logic based power management strategy using topographic data for an electric vehicle with a battery-ultracapacitor energy storage. COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering, 34(1), 173-188.
http://dx.doi.org/10.1108/COMPEL-11-2013-0388
[5] M. Michalczuk, Fuzzy logic control of electric vehicle, http://www.mathworks.com/matlabcentral/fileexchange/48250