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.

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.

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.

The Fuel_LF‐RTO strategy is real‐time optimization (RTO) strategy proposed here to find the optimal values of fueling for the polymer electrolyte membrane fuel cell hybrid power sources under unknown load profile, which is the case of fuel cell vehicle. The proposed optimization strategy is based on global extremum seeking (GES) algorithm and load‐following (LF) control for air and fuel flows. The results show the performance obtained with Fuel_LF‐RTO strategy in comparison with the Static Feed‐Forward strategy. The performance was estimated for constant and variable load. The FC system efficiency and the fuel consumption efficiency for maximum load of 8 kW can increase with up to 1.88% and 11.26 W lpm−1 in comparison with the sFF RTO strategy. Also, the fuel economy is 27.36 L during the 8 kW/12 s constant load cycle, which means an economy of 136.8 lpm. This performance is highlighted for constant load in range 2 to 8 kW, which represents 0.33% and 1.25% from nominal power of the 6 kW FC stack used in this study. Also, the performance was estimate for variable load considering the fuel economy, which can be up to 21.86 l during the 6.25 kW/12 s pulsed load cycle.

This paper proposes a Real-time optimization (RTO) strategy for Fuel Cell Hybrid Power Sources based on Global Extremum Seeking (GES) control of the air flow. The performance is shown in comparison with Static Feed-Forward RTO strategy.