Marek Michalczuk

Fuzzy logic based power management strategy using topographic data for an electric vehicle with a battery-ultracapacitor energy storage

Purpose – The purpose of this paper is to provide high-efficiency and high-power hybrid energy source for an urban electric vehicle. A power management strategy based on fuzzy logic has been introduced for battery-ultracapacitor (UC) energy storage. Design/methodology/approach – The paper describes the design and construction of on-board hybrid source. The proposed energy storage system consists of battery, UCs and two DC/DC interleaved converters interfacing both storages. A fuzzy-logic controller (FLC) for the hybrid energy source is developed and discussed. Control structure has been tested using a non-mobile experimental setup. Findings – The hybrid energy storage ensures high-power ability. Flexibility and robustness offered by the FLC give an easy accessible method to provide a power management algorithm extended with additional input information from road infrastructure or other vehicles. In the presented research, it was examined that using information related to the topography of the road in the ...

Fuzzy logic control of a hybrid battery-ultracapacitor energy storage for an urban electric vehicle

This paper presents simulation studies and preliminary experimental results related to a hybrid battery-ultracapacitor energy source for an urban electric car. A proposal of energy management strategy based on fuzzy logic is introduced. Control strategy for the hybrid source is designed to achieve high-efficiency and high-power source for the vehicle with a relatively small battery storage. Simulation studies show the possibility to use information from a navigation system to improve performance of the source.

Powertrain system with the ultracapacitor-based auxiliary energy storage for an urban battery electric vehicle

This paper presents a powertrain system for an urban electric vehicle. The powertrain system consists of a hybrid energy source (battery storage and ultracapacitors) and drivetrain system (two in-wheel outer-rotor PMSM motors). Battery performance improvement, has been achieved by supporting it with ultracapacitor energy storage. Power flow control using fuzzy logic controller is presented in detail. An electronic differential algorithms have been implemented and tested.

Particle swarm optimization of the fuzzy logic controller for a hybrid energy storage system in an electric car

This paper describes the particle swarm optimization of the fuzzy logic controller for a hybrid energy storage system in an 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 has been proposed to determine the weights of rules. A simulation and experimental validation of the power management algorithm is also introduced in this paper.

Experimental parameter identification of battery-ultracapacitor energy storage system

This paper introduces a simulation model of battery-ultracapacitor hybrid energy storage system. The study aims at creating adequate model to investigate the benefits of energy storage system hybridization for an electric vehicle. The experimental tests have been carried out in order to identify the parameters of lithium battery and ultracapacitor. The dynamic models are able to simulate terminal voltage of energy storage including the dependencies on state of charge and temperature.

Particle swarm optimization of the multioscillatory LQR for a three-phase grid-tie converter

This paper presents an evolutionary optimization of the linear-quadratic (LQ) current controller for a three-phase grid-tie voltage source converter with an L-type input filter. The current control system is equipped with multi-oscillatory terms, which enable the converter to obtain nearly sinusoidal shape and balanced input currents under unbalanced and distorted grid voltage conditions. The augmentation of the state vector to include additional states which describe dynamics of disturbances increases the number of weights to be selected for a cost function in the LQR procedure design. Therefore, it is proposed that optimal weighting factors are sought using particle-swarm-based method. Finally, the simulational tuning based on the linear model and the numerical verification based on a non-linear model of the system with a pulse width modulator are addressed. Streszczenie. Artykuł prezentuje optymalizację ewolucyjną liniowo-kwadratowego regulatora prądu dla trójfazowego przekształtnika sieciowego z filtrem wejściowym typu L. Układ regulacji prądu jest wypozażony w człony oscylacyjne co pozwala na kształtowanie niemal sinusoidalnych i symetrycznych prądów wejściowych w warunkach występowania wyższych harmonicznych i asymetrii napięć sieci. Rozszerzenie wektora stanu o dodatkowe stany opisujące dynamikę zakłóceń zwiększa liczbę wag, które należy dobrać dla funkcji celu ujętej w procedurze projektowania LQR. Dlatego zaproponowano dobór optymalnych wsółczynników wagowych przy użyciu optymalizacji metodą roju cząstek. Finalnie zostały omówione strojenie symulacyjne na modelu liniowym oraz weryfikacja numeryczna na modelu nieliniowym z modulatorem szerokości impulsów. (Optymalizacja rojem cząstek regulatora liniowo-kwadratowego z członami oscylacyjnymi dla trójfazowego przekształtnika sieciowego)