An adaptive state machine based energy management strategy for a multi-stack fuel cell hybrid electric vehicle

This paper aims at designing an online energy management strategy (EMS) for a multi-stack fuel cell hybrid electric vehicle (FCHEV) to enhance the fuel economy as well as the fuel cell stacks (FCSs) lifetime. In this respect, a two-layer strategy is proposed to share the power among four FCSs and a battery pack. The first layer (local to each FCS) is held solely responsible for constantly determining the real maximum power and efficiency of each stack since the operating conditions variation and ageing noticeably influence stacks' performance. This layer is composed of a FCS semi-empirical model and a Kalman filter. The utilized filter updates the FCS model parameters to compensate for the FCSs' performance drifts. The second layer (global management) is held accountable for splitting the power among components. This layer uses two inputs per each FCS, updated maximum power and efficiency, as well as the battery state of charge (SOC) and powertrain demanded power to perform the power sharing. The proposed EMS, called adaptive state machine strategy, employs the first two inputs to sort the FCSs out and the other inputs to do the power allocation. The ultimate results of the suggested strategy are compared with two commonly used power sharing methods, namely Daisy Chain and Equal Distribution. The results of the suggested EMS indicate promising improvement in the overall performance of the system. The performance validation is conducted on a developed test bench by means of hardware-in-the-loop (HIL) technique

Efficiency enhancement of an open cathode fuel cell through a systemic management

This paper addresses the design of a systemic management to improve the energetic efficiency of an open cathode proton exchange membrane fuel cell (PEMFC) in a hybrid system. Unlike the other similar works, the proposed approach capitalizes on the usage of both thermal management strategy and current control to meet the requested power from the system by the minimum fuel consumption. To do so, firstly, an experimentally based 3D mapping is performed to relate the requested power form the PEMFC to its operating temperature and current. Secondly, the reference temperature which leads to gaining the demanded power by the minimum current level is determined to minimize the hydrogen consumption. Finally, the temperature control is formulated by an optimized fuzzy logic scheme to reach the determined reference temperature by acting on the cooling fan of the PEMFC system, whilst the current is being regulated by its controller. The inputs of the fuzzy controller are the PEMFC current and temperature error and the sole output is the duty factor of the fan. The proposed methodology is tested on an experimental test bench to be better evaluated in a real condition. The obtained results from the proposed systemic management indicate promising enhancement of the system efficiency compared to a commercial controller. The proposed method of this work is extendable and applicable in fuel cell hybrid electric vehicles

An adaptive power distribution scheme for hybrid energy storage system to reduce the battery energy throughput in electric vehicles

The battery/supercapacitor (SC) hybrid energy storage system (HESS) is widely applied in electric vehicles (EVs) in recent years due to the hybrid system which combines the benefits of both devices. This paper proposes an adaptive power distribution scheme for battery/SC HESS to maximise the usage of SC according to its stored energy and load current. In the approach, the low-pass filter is developed with adaptive algorithm to calculate the suitable cut-off frequency to allocate the power demand between the battery and SC. The approach can adjust the cut-off frequency but not change the structure of the control system, and thus its original property of simple implementation and stability is not affected. The comprehensive simulation study verifies the effectiveness of the proposed adaptive power distribution scheme in a battery/SC HESS and its stability is further validated using Lyapunov method. The result shows that the adaptive method performs better than a traditional control system with 20%–40% less battery energy throughput during operation and can adjust the dynamic response of the HESS according to the energy capacity of SC to further improve system efficiency. The proposed adaptive power distribution scheme is verified able to extend the service life of the HESS system in EV applications

Optimal Control of Hybrid Systems and Renewable Energies

This book is a collection of papers covering various aspects of the optimal control of power and energy production from renewable resources (wind, PV, biomass, hydrogen, etc.). In particular, attention is focused both on the optimal control of new technologies and on their integration in buildings, microgrids, and energy markets. The examples presented in this book are among the most promising technologies for satisfying an increasing share of thermal and electrical demands with renewable sources: from solar cooling plants to offshore wind generation; hybrid plants, combining traditional and renewable sources, are also considered, as well as traditional and innovative storage systems. Innovative solutions for transportation systems are also explored for both railway infrastructures and advanced light rail vehicles. The optimization and control of new solutions for the power network are addressed in detail: specifically, special attention is paid to microgrids as new paradigms for distribution networks, but also in other applications (e.g., shipboards). Finally, optimization and simulation models within SCADA and energy management systems are considered. This book is intended for engineers, researchers, and practitioners that work in the field of energy, smart grid, renewable resources, and their optimization and control

Advanced Modeling and Research in Hybrid Microgrid Control and Optimization

This book presents the latest solutions in fuel cell (FC) and renewable energy implementation in mobile and stationary applications. The implementation of advanced energy management and optimization strategies are detailed for fuel cell and renewable microgrids, and for the multi-FC stack architecture of FC/electric vehicles to enhance the reliability of these systems and to reduce the costs related to energy production and maintenance. Cyber-security methods based on blockchain technology to increase the resilience of FC renewable hybrid microgrids are also presented. Therefore, this book is for all readers interested in these challenging directions of research

A review of commercialisation mechanisms for carbon dioxide removal

The deployment of carbon dioxide removal (CDR) needs to be scaled up to achieve net zero emission pledges. In this paper we survey the policy mechanisms currently in place globally to incentivise CDR, together with an estimate of what different mechanisms are paying per tonne of CDR, and how those costs are currently distributed. Incentive structures are grouped into three structures, market-based, public procurement, and fiscal mechanisms. We find the majority of mechanisms currently in operation are underresourced and pay too little to enable a portfolio of CDR that could support achievement of net zero. The majority of mechanisms are concentrated in market-based and fiscal structures, specifically carbon markets and subsidies. While not primarily motivated by CDR, mechanisms tend to support established afforestation and soil carbon sequestration methods. Mechanisms for geological CDR remain largely underdeveloped relative to the requirements of modelled net zero scenarios. Commercialisation pathways for CDR require suitable policies and markets throughout the projects development cycle. Discussion and investment in CDR has tended to focus on technology development. Our findings suggest that an equal or greater emphasis on policy innovation may be required if future requirements for CDR are to be met. This study can further support research and policy on the identification of incentive gaps and realistic potential for CDR globally