This paper presents a Fuel Cell Electric Vehicle (FCEV) powertrain development and optimization, aiming to minimize hydrogen consumption. The vehicle is a prototype that run at the Shell Eco-marathon race and its powertrain is composed by a PEM fuel cell, supercapacitors and a DC electric motor. The supercapacitors serve as an energy buffer to satisfy the load peaks requested by the electric motor, allowing a smoother (and closer to a stationary application) working condition for the fuel cell. Thus, the fuel cell can achieve higher efficiency rates and the fuel consumption is minimized.Several models of the powertrain were developed using MATLAB-Simulink and then experimentally validated in laboratory and on the track. The proposed models allow to evaluate two main arrangements between fuel cell and supercapacitors: 1) through a DC/DC converter that sets the FC current to a desired value; 2) using a direct parallel connection between fuel cell and supercapacitors.The results obtained with the direct parallel connection (with the appropriate sizing of the overall capacity) have highlighted a significant efficiency advantage, while the DC/DC converter insertion enables an improved control of the fuel cell current and requires a smaller capacitance.Furthermore, a sizing methodology for the supercapacitors capacitance is proposed for both layouts: with the DC/DC converter it mainly depends on the energy range provided by supercapacitors to the electric motor, while in the direct parallel connection the supercapacitors sizing is outlined by concurrently evaluating the circuit’s predicted hydrogen consumption and granting the most suitable conditions to increase the fuel cell performance.Finally, the results obtained from the model were validated by comparing them with experimental data obtained in the laboratory and on the track.

This article addresses a common issue in the design of battery electric vehicles (BEVs) by introducing a comprehensive methodology for the modeling and simulation of BEVs, referred to as the “PerfECT Design Tool”. The primary objective of this study is to provide engineers and researchers with a robust and streamlined approach for the early stages of electric vehicle (EV) design, offering valuable insights into the performance, energy consumption, current flow, and thermal behavior of these advanced automotive systems. Recognizing the complex nature of contemporary EVs, the study highlights the need for efficient design tools that facilitate decision-making during the conceptual phases of development. The PerfECT Design Tool is presented as a multi-level framework, divided into four logically sequential modules: Performance, Energy, Currents, and Temperature. These modules are underpinned by sound theoretical foundations and are implemented using a combination of MATLAB/Simulink and the vehicle dynamics software VI-CRT. The research culminates in the validation of the model through a series of experimental maneuvers conducted with a Tesla Model 3, establishing its accuracy in representing the mechanical, electrical, and thermal behavior of BEVs. The study’s main findings underscore the viability of the design tool as an asset in the initial phases of BEV design. Beyond its primary application, the tool holds promise for broader utilization, including the development of active control systems, advanced driver assistance systems (ADAS), and solutions for autonomous driving within the domain of electric vehicles.

Powertrain electrification is undoubtedly recognized as a major trend in the automotive industry. The elimination of the internal combustion engine opens to different vehicles architecture designs, to improve habitability and reduce cost. The paper focus on an All-Wheel-Drive Full Electric high-performance vehicle equipped with wheel-hub motors, a layout that offers a significant potential in controlling each wheel individually. The objective is to develop a control algorithm capable of handling wheels torques independently to enhance vehicle's dynamic, keeping into consideration the model's energy performance. The control algorithm is entirely developed in Matlab-Simulink and implemented in the vehicle dynamic model, in a co-simulation environment with VI-CarRealTime software. Offline simulations are performed to tune the controllers and evaluate their impact on vehicle dynamics and energy efficiency. Finally, the model is tested in a real static simulator to be validated and to have a subjective interpretation of the dynamic behavior of the vehicle. Handling improvements are evaluated through a racetrack lap time performed by the VI-Grade virtual driver. Energy efficiency protocols instead will be assessed by monitoring the battery State of Charge variation and their impact on vehicle's behavior will be analyzed on the static simulator. The results point out to an improvement in the lap time thanks to the more agile and less understeering vehicle. Energy optimization algorithms and regenerative braking displays a promising energy reduction without compromising vehicle dynamics. The same racetrack from the offline simulations is used to test the model on the static simulator. Torque vectoring impact on driver's feeling is found to be noticeable and helpful in improving vehicle's response during cornering while energy optimization protocols are not affecting the dynamic performance.

Humidity and temperature have an essential influence on PEM fuel cell system performance. The water content within the polymeric membrane is important for enhancing proton conduction and achieving high efficiency of the system. The combination of non-stationary operation requests and the variability of environment conditions poses an important challenge to maintaining optimal membrane hydration. This paper presents a humidification and thermal control system, to prevent the membrane from drying. The main characteristics of such a device are small size and weight, compactness and robustness, easy implementation on commercial fuel cell, and low power consumption. In particular, the NTHS method was studied in a theoretical approach, tested and optimized in a laboratory and finally applied to a PEMFC of 1 kW that supplied energy for the prototype vehicle IDRA at the Shell Eco-Marathon competition. Using a specific electronic board, which controls several variables and decides the optimal reaction air flow rate, the NTHS was managed. Furthermore, the effects of membrane drying and electrode flooding were presented.

This paper describes the design process of the monocoque for IDRAkronos, a three-wheeler hydrogen prototype focused on fuel efficiency, made to compete at the Shell Eco-Marathon event. The vehicle takes advantage of the lightweight and high mechanical performance of carbon fiber to achieve minimal mass and optimized fuel consumption. Based on previous experiences and background knowledge, the authors describe their work toward a design that integrates aerodynamic performance, style, structural resistance and stiffness. A portrayal of the objectives, load cases, simulations and production process—that lead to a final vehicle winner of the Design Award and 1st place general at the 2016 competition—is presented and discussed.