Parameter Identification of PEM Fuel Cell Using Quantum-Based Optimization Method

Parameter identification of proton exchange membrane (PEM) fuel cells using quantum-based optimization method (QBOM) is presented in this paper. The QBOM is an algorithm that is adapted from certain elements of quantum computing aimed for use in a wider class of search and optimization problems. QBOM is composed of qubits and quantum gates. The quantum gate evolves the qubits until the desired objective is achieved, while qubits maintain the information in a superposition for all states. This novel optimization technique presents innovative insight in finding the best answer. Unlike other evolutionary search mechanism philosophies, the QBOM utilizes quantum phenomena to allocate the optimum, while the evolutionary algorithms seek to find the optimal solution using the available information including the best found to assemble the search mechanism with certain rules to avoid trapping in local minima. The proposed method is applied to 1.2 kW Ballard Nexa fuel cell to identify the exact parameters and has been successfully tested experimentally. Results based on parameter identification, simulation and experimental measurements are compared for validation purposes. The outcomes are very encouraging and prove that QBOM is very applicable in parameter optimization of PEM fuel cell.