Mariana Iliescu

Bio: Mariana Iliescu is an academic researcher from Institute of Company Secretaries of India. The author has contributed to research in topics: Hybrid power & Proton exchange membrane fuel cell. The author has an hindex of 6, co-authored 18 publications receiving 109 citations.

Fuel Cell Electric Vehicles—A Brief Review of Current Topologies and Energy Management Strategies

Abstract: With the development of technologies in recent decades and the imposition of international standards to reduce greenhouse gas emissions, car manufacturers have turned their attention to new technologies related to electric/hybrid vehicles and electric fuel cell vehicles. This paper focuses on electric fuel cell vehicles, which optimally combine the fuel cell system with hybrid energy storage systems, represented by batteries and ultracapacitors, to meet the dynamic power demand required by the electric motor and auxiliary systems. This paper compares the latest proposed topologies for fuel cell electric vehicles and reveals the new technologies and DC/DC converters involved to generate up-to-date information for researchers and developers interested in this specialized field. From a software point of view, the latest energy management strategies are analyzed and compared with the reference strategies, taking into account performance indicators such as energy efficiency, hydrogen consumption and degradation of the subsystems involved, which is the main challenge for car developers. The advantages and disadvantages of three types of strategies (rule-based strategies, optimization-based strategies and learning-based strategies) are discussed. Thus, future software developers can focus on new control algorithms in the area of artificial intelligence developed to meet the challenges posed by new technologies for autonomous vehicles.

Design and Simulation of Romanian Solar Energy Charging Station for Electric Vehicles

Abstract: Since mid 2010, petrol consumption in the transport sector has increased at a higher rate than in other sectors. The transport sector generates 35% of the total CO2 emissions. In this context, strategies have been adopted to use clean energy, with electromobility being the main directive. This paper examines the possibility of charging electric vehicle batteries with clean energy using solar autochthonous renewable resources. An isolated system was designed, dimensioned, and simulated in operation for a charging station for electric vehicles with photovoltaic panels and batteries as their main components. The optimal configuration of the photovoltaic system was complete with improved Hybrid Optimization by Genetic Algorithms (iHOGA) software version 2.4 and we simulated its operation. The solar energy system has to be designed to ensure that the charging station always has enough electricity to supply several electric vehicles throughout all 24 h of the day. The main results were related to the energy, environmental, and economic performance achieved by the system during one year of operation.

Hybrid Electric Powertrain with Fuel Cells for a Series Vehicle

Abstract: Recent environmental and climate change issues make it imperative to persistently approach research into the development of technologies designed to ensure the sustainability of global mobility. At the European Union level, the transport sector is responsible for approximately 28% of greenhouse gas emissions, and 84% of them are associated with road transport. One of the most effective ways to enhance the de-carbonization process of the transport sector is through the promotion of electric propulsion, which involves overcoming barriers related to reduced driving autonomy and the long time required to recharge the batteries. This paper develops and implements a method meant to increase the autonomy and reduce the battery charging time of an electric car to comparable levels of an internal combustion engine vehicle. By doing so, the cost of such vehicles is the only remaining significant barrier in the way of a mass spread of electric propulsion. The chosen method is to hybridize the electric powertrain by using an additional source of fuel; hydrogen gas stored in pressurized cylinders is converted, in situ, into electrical energy by means of a proton exchange membrane fuel cell. The power generated on board can then be used, under the command of a dedicated management system, for battery charging, leading to an increase in the vehicle’s autonomy. Modeling and simulation results served to easily adjust the size of the fuel cell hybrid electric powertrain. After optimization, an actual fuel cell was built and implemented on a vehicle that used the body of a Jeep Wrangler, from which the thermal engine, associated subassemblies, and gearbox were removed. Once completed, the vehicle was tested in traffic conditions and its functional performance was established.

Real-time strategy to optimize the fuel flow rate of fuel cell hybrid power source under variable load cycle

Abstract: A real-time optimization (RTO) strategy for the Fuel Cell Hybrid Power Sources (FCHPS) is proposed in this paper. The optimization strategy is based on the Global Extremum Seeking (GES) search of the optimal value of the fuel flow rate of the FC stack. The airflow rate is controlled by the FC current as in the Static Feed-Forward (sFF) RTO strategy, where both fueling flow rates are controlled by the FC current. The performance of the proposed Fuel_GES-RTO strategy is shown in comparison with the sFF-RTO strategy for constant and variable load. In the last case, a Load-Following (LF) control of the boost converter is used for both strategies.

Optimal Photovoltaic/Battery Energy Storage/Electric Vehicle Charging Station Design Based on Multi-Agent Particle Swarm Optimization Algorithm

Abstract: In order to effectively improve the utilization rate of solar energy resources and to develop sustainable urban efficiency, an integrated system of electric vehicle charging station (EVCS), small-scale photovoltaic (PV) system, and battery energy storage system (BESS) has been proposed and implemented in many cities around the world. This paper proposes an optimization model for grid-connected photovoltaic/battery energy storage/electric vehicle charging station (PBES) to size PV, BESS, and determine the charging/discharging pattern of BESS. The multi-agent particle swarm optimization (MAPSO) algorithm solves this model is solved, which combines multi-agent system (MAS) and the mechanism of particle swarm optimization (PSO). In this model, a load simulation model is presented to simulate EV charging patterns and to calculate the EV charging demand at each time interval. Finally, a case in Shanghai, China is conducted and three scenarios are analyzed to prove the effectiveness of the proposed model. A comparative analysis is also performed to show the superiority of MAPSO algorithm.

Control Of Fuel Cell Power Systems Principles Modeling Analysis And Feedback Design

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