Lucia Gauchia

Black-Box Model, Identification Technique and Frequency Analysis for PEM Fuel Cell With Overshooted Transient Response

Fuel cells are one of the most promising energy sources, especially for onboard applications. However, fuel cells present several drawbacks, such as slow dynamic response, load-dependent voltage, and unidirectional power flow, which cause an inappropriate vehicle operation. So, secondary energy sources and power converters must be implemented in order to satisfy fast changes in the current load and to store the energy delivered by the load if regenerative braking is intended. Taking into account the number and nature of the power converters, loads, secondary energy sources, and the possibilities for the control strategies, the design of a power distribution architecture based on fuel cells for transport applications is a complex task. In order to address these architectures, modeling and simulation design tools at system level are essential. This paper proposes a complete fuel cell black-box model which reproduces the behavior of a commercial fuel cell with overshooted transient response. The identification technique applied to parameterize the model components, based on manufacturers datasheets and a test based on load steps, is explained thoroughly. In addition, if only the fuel cell frequency response and manufacturers datasheet are available, an alternative parameterization methodology based on the fuel cell frequency response is presented. The fuel cell black-box model is validated experimentally using a commercial proton exchange membrane fuel cell. Two different parameterizations are carried out with the aim of verifying the robustness of both the fuel cell model and the proposed identification methodology.

Simulation and Analysis of the Effect of Real-World Driving Styles in an EV Battery Performance and Aging

This paper presents the large data analysis of the real-world driving cycles and studies the effect of different driving styles on the electric vehicle (EV) battery performance and aging. For this study, a MATLAB-based software tool, real EV cycle (REV-cycle) analyzer, is developed. The real-world driving data are recorded from the I-80 highway, CA, USA. In this study, driving cycles are classified into three styles as aggressive, mild, and gentle driving based on their average acceleration. Also, two standard driving cycles (EUDC and HWFET) are simulated by the software and the results are compared. The results show that the real driving cycles are very different from the standard cycles. Also, it is observed that the traffic flow affects the driving style, as the drivers tend to drive more aggressive during the light traffic hours of the highway, while the heavy traffic limits the drivers aggressive behavior. On the other hand, the driving style has considerable effect on the energy consumption and the battery aging. The aggressive driving style demands higher average power from the battery compared to the mild and gentle driving style. From the aging point of view, the aggressive driving style leads to higher Crate demand from the battery and it expedited the capacity fade process compared to the mild and gentle driving styles.

Electric Vehicle Battery Cycle Aging Evaluation in Real-World Daily Driving and Vehicle-to-Grid Services

In this paper, battery lifetime estimation of an electric vehicle (EV) using different driving styles on arterial roads integrating recharging scenarios in the neighborhood of the vehicle-to-grid integration is studied. The real-world driving cycles from a fleet of connected vehicles are evaluated in an EV model with different charging options. Daily utility services are added to the simulations to explore the whole day performance of the battery and its daily degradation. Fifty driving cycles from different drivers on arterial roads are classified into aggressive, mild, and gentle drivers based on their driving acceleration behavior. The standard levels 1 and 2 chargers are considered for recharging and the frequency regulation, and peak shaving and solar energy storage are assumed for the daily ancillary services. The results indicate that the aggressive driving and recharging behavior have significant effect on the battery life reduction. In addition, the daily utility services impose extra degradation of the battery. Also, the effect of temperature change on the battery degradation is explored. Simulation of active versus passive thermal management systems in three different climates shows the significant impact of the battery temperature on its capacity fade.

Off-the-Shelf and Flexible Hybrid Frequency and Time Domain Experimental Architecture Setup for Electrochemical Energy Modules Testing Under Realistic Operating Conditions

This paper proposes a standard and flexible test bench architecture for the testing and modeling of electrochemical energy modules. It also presents a comprehensive methodology that enables to obtain accurate models under realistic operating conditions with a low computational cost. For this purpose, three different configuration modes of the experimental architecture setup are introduced. Finally, the test bench architecture and the experimental methodology proposed have been validated by the modeling and testing of a Li-ion battery pack and a supercapacitor module.

REV-cycle: A MATLAB-based tool for large-data analysis of real-life driving cycles for electric vehicles

Electric vehicles are increasingly being adopted due to environmental awareness and competitive technical performance and reducing prices. Their research and development has sometimes relied on the use of standard driving cycles. However, these cycles cannot reproduce the variations of traffic flow in real world. That is why in this paper we develop a software tool able to analyze real-life driving cycles for electric vehicles. To do so, a driving trajectory process tool is used to obtain large data for vehicles driving in the same stretch of highway. To show the performance of the developed tool, sample cycles are analyzed and simulated for electric vehicles automatically in the REV-Cycle (Real Electric Vehicle Cycle analyzer) software presented.

Guest Editorial Special Section on Energy Storage Systems

Energy storage is revolutionizing transportation by proving a sustainable alternative to fossil fuels, and opening new opportunities as flexible grid bidirectional storage through vehicle-to-grid services. In order to fully exploit these new transportation opportunities, advances still need to be achieved in energy storage, and batteries, in particular, to improve range, cost, and lifetime. Current trends show a higher penetration in road transportation compared with other sectors, but with promising roadmaps for marine, aerospace, and rail sectors. Therefore, the body of work required to achieve these roadmaps spans from electrochemical, thermal, and electrical simulations to better understand the battery operation to system integration design within the powertrain and the grid. This Special Section provides with new knowledge on the full research and development spectrum, by presenting battery electrochemical and thermal modeling techniques, design of storage solutions for electrified vehicle recharging stations, energy management for electric vehicles and simulation, and design and deployment of energy storage for rail and material handling applications.

Modeling, parameterization, and benchmarking of a lithium ion electric bicycle battery

A lithium-ion battery from an electric bicycle conversion kit is tested and modeled using electrochemical impedance spectroscopy, and the hybrid pulse power characterization test (HPPC). Equivalent circuit model parameterizations are obtained from both time and frequency domain fitting and compared. Parameterization methods are described and a novel quadratic programmed-based two stage parameter fitting algorithm is presented to process and generate model parameters. Experimental data is applied to the proposed algorithm to assess fitting performance. The battery model is validated by real-life riding cycles. Additional electric bicycle benchmarking tests are performed to assess real-world battery performance under a variety of riding conditions and at different assistance levels. The brief correlation between tiredness and assistance levels is investigated.

Dynamic Modelling and Simulation of Electrochemical Energy Systems for Electric Vehicles

The current energy scenery is dominated by fossil fuels, especially oil. This dependency is turning critical due to the reducing reserves, uncertain oil resources, and political and economical ramifications of a concentration of fossil fuel reserves in a limited number of regions. The transportation sector is especially affected by this situation and needs to develop new energy vectors and systems to reduce the oil dependency whilst attending to environmental issues. Therefore, vehicle manufacturers are turning to hybrid and electric vehicles. Hybrid vehicles combine an internal combustion engine (ICE) with energy storage systems, which allows reducing the installed power of the ICE, and consequently the fuel consumption and pollutant emissions. With this power train, the user is capable of driving in a pure electric mode, through the energy storage system (normally batteries), or in a hybrid mode with both ICE and storage for more challenging driving cycles. Electric vehicles are especially interesting due to the exclusion of the ICE, which reduces to zero the emissions, and presents a higher efficiency of the power train and environmentally friendly operation. However, even if these reasons are activating its interest, there are several drawbacks which should be solved before reaching a mass production scale. Some of these issues include the development of energy technologies able to guarantee an adequate vehicle range, attractive power ratings and safe, simple and fast recharge. Nowadays there is no electric energy storage technology which can exhibit both high energy and power densities, necessary to meet range and accelerating requirements. Therefore, there is an intensive research to develop new materials for electrochemical energy devices and to hybridize electrochemical energy systems to reach the necessary power and energy specifications. The most popular technologies are Ni-Mh and Li-based batteries, which present higher energy densities than classic Pb-acid batteries. However, these technologies cannot achieve the range obtained with fossil fuels. Therefore, other energy systems, such as fuel cells or flow batteries are being studied as part of a hybrid electric vehicle power train. Finally, this energy system research should be done taking into account the particular situation of transportation, where the weight, volume and cost of the systems included are relevant for a successful and massive use of the electric vehicle. To carry out this research in the final application stage of electrochemical systems, it is necessary to be able to test, model and simulate this system in real operating conditions.