A Firefly Algorithm Optimization-Based Equivalent Consumption Minimization Strategy for Fuel Cell Hybrid Light Rail Vehicle

Abstract

To coordinate multiple power sources properly, this paper presents an optimal control strategy for a fuel cell/battery/supercapacitor light rail vehicle. The proposed strategy, which uses the firefly algorithm to optimize the equivalent consumption minimization strategy, improves the drawback that the conventional equivalent consumption minimization strategy takes insufficient account of the global performance for the vehicle. Moreover, the strategy considers the difference between the two sets of optimized variables. The optimization objective is to minimize the daily operating cost of the vehicle, which includes the total fuel consumption, initial investment, and cycling costs of power sources. The selected case study is a 100% low-floor light rail vehicle. The advantages of the proposed strategy are investigated by comparison with the operating mode control, firefly algorithm-based operating mode control, and equivalent consumption minimization strategy. In contrast to other methods, the proposed strategy shows cost reductions of up to 39.62% (from operating mode control), 18.28% (from firefly algorithm-based operating mode control), and 13.81% (from equivalent consumption minimization strategy). In addition, the proposed strategy can reduce fuel consumption and increase the efficiency of the fuel cell system.

Design of an Equivalent Consumption Minimization Strategy-Based Control in Relation to the Passenger Number for a Fuel Cell Tram Propulsion

“…The PEM model is based on the equivalent circuit, where the electrochemical model plays a pivotal role. The Nernst voltage, namely the ideal voltage, is the first term of Equations (9)- (10) and is the input of the voltage source. A particular focus is on the partial pressures, obtained by the derivative of the gas law, solved through the Laplace transformation [7].…”

“…The PEM current is imposed by the DC/DC converter, according to the control strategy decisions, while the real voltage is achieved by the difference between the Nernst voltage and the activation (V act ), ohmic (V ohm ), and concentration losses (V conc ), as shown in Equations (9)- (10). The former are due to the slow kinetics of the reactions and they are good represented by the Tafel equation, calculated as the logarithm of the ratio between fuel cell (I FC ) and exchange current (I 0 ).…”

“…The ohmic losses are caused by the internal resistance of the system, achieved using Ohm's law. The latter, namely the concentration losses, occur at high currents, for the gradient of the reactant concentration; this phenomenon is approximated by the last terms of Equations (9)- (10), function of the operative and maximum (I max ) fuel cell currents.…”

“…In [9], Hong et al proposed an energy management strategy based on a dynamic following coefficient for an FC-B train; the control system can maintain the hybrid system efficiency above 44%, with a strong capacity to sustain the battery state of charge. In [10], Zhang et al implemented a firefly algorithm to optimize the standard equivalent consumption minimization strategy (ECMS) for an FC-B-SC tram. An accurate analysis is conducted and the strategy designed is compared with other algorithms, based on operative mode control and ECMS, achieving operating cost and fuel consumption saving (more than 13.81% and 20.75%) and FC efficiency improvements (more than 0.5%).…”

Improvement of Firefly Algorithm using Particle Swarm Optimization and Gravitational Search Algorithm

“…Improvement of Firefly Algorithm (FA) in [5] with Asexual Reproduction Optimization Algorithm (ARO), in [6] with Artificial Bee Colony (ABC) and in reference [7] using Pattern Search (PS) are done. There are also many research on the application of the firefly algorithm to various issues [12][13][14][15]. Such as these, Engineering optimization problems can be addressed.…”