http://ieeexplore.ieee.org/iel5/5610941/5624686/05624745.pdf

Power electronics

Review of wearable thermoelectric energy harvesting: From body temperature to electronic systems

Review on current research of materials, fabrication and application for bipolar plate in proton exchange membrane fuel cell

Proton-conducting oxides are a class of solid-state ion-conducting ceramic materials that demonstrate significant hydrogen ion (proton) conductivity at intermediate temperatures (e.g., 300–700 °C). They are garnering significant attention due to several unique characteristics that distinguish them from both higher temperature oxygen ion conducting oxides and lower temperature proton-conducting polymers. By enabling proton-mediated electrochemistry under both dry and wet environments at moderate temperatures, protonic ceramics provide unique opportunities to enhance or synergize a diverse range of complementary electrochemical and thermochemical processes. Because of this potential, significant efforts have been devoted to advancing numerous energy-related applications using these materials. This review aims to comprehensively summarize these applications and analyze the most up-to-date and future developments of proton-conducting oxides. We aim to bring together this diverse subject matter by integrating the fundamentals of proton-conducting oxides with application-oriented insights. We begin with a historical roadmap, followed by a basic overview of the materials, theories and fundamentals, and fabrication and processing technologies underlying the field. The central section of our review summarizes major applications and developments of proton-conducting ceramics, ranging from maturing applications approaching commercialization to embryonic technologies just now emerging from the lab. These include protonic ceramic fuel cells, protonic ceramic electrolysis cells, reversible protonic ceramic electrochemical cells, protonic ceramic membrane reactors, and protonic ceramic electrochemical reactors. For each application, we analyze both the prospects and challenges and offer recommendations for future research directions so that tomorrow's researchers can continue to advance the development and commercialization of these fascinating materials.

Proton-conducting oxides for energy conversion and storage

Review on the research of hydrogen storage system fast refueling in fuel cell vehicle

PEM fuel cell system control: A review

In the last few years, intensive research has been done to enhance artificial intelligence (AI) using optimization techniques. In this paper, we present an extensive review of artificial neural networks (ANNs) based optimization algorithm techniques with some of the famous optimization techniques, e.g., genetic algorithm (GA), particle swarm optimization (PSO), artificial bee colony (ABC), and backtracking search algorithm (BSA) and some modern developed techniques, e.g., the lightning search algorithm (LSA) and whale optimization algorithm (WOA), and many more. The entire set of such techniques is classified as algorithms based on a population where the initial population is randomly created. Input parameters are initialized within the specified range, and they can provide optimal solutions. This paper emphasizes enhancing the neural network via optimization algorithms by manipulating its tuned parameters or training parameters to obtain the best structure network pattern to dissolve the problems in the best way. This paper includes some results for improving the ANN performance by PSO, GA, ABC, and BSA optimization techniques, respectively, to search for optimal parameters, e.g., the number of neurons in the hidden layers and learning rate. The obtained neural net is used for solving energy management problems in the virtual power plant system.

Artificial Neural Networks Based Optimization Techniques: A Review

This paper reviews energy storage systems, in general, and for specific applications in low-cost micro-energy harvesting (MEH) systems, low-cost microelectronic devices, and wireless sensor networks (WSNs). With the development of electronic gadgets, low-cost microelectronic devices and WSNs, the need for an efficient, light and reliable energy storage device is increased. The current energy storage systems (ESS) have the disadvantages of self-discharging, energy density, life cycles, and cost. The ambient energy resources are the best option as an energy source, but the main challenge in harvesting energy from ambient sources is the instability of the source of energy. Due to the explosion of lithium batteries in many cases, and the pros associated with them, the design of an efficient device, which is more reliable and efficient than conventional batteries, is important. This review paper focused on the issues of the reliability and performance of electrical ESS, and, especially, discussed the technical challenges and suggested solutions for ESS (batteries, supercapacitors, and for a hybrid combination of supercapacitors and batteries) in detail. Nowadays, the main market of batteries is WSNs, but in the last decade, the world’s attention has turned toward supercapacitors as a good alternative of batteries. The main advantages of supercapacitors are their light weight, volume, greater life cycle, turbo charging/discharging, high energy density and power density, low cost, easy maintenance, and no pollution. This study reviews supercapacitors as a better alternative of batteries in low-cost electronic devices, WSNs, and MEH systems.

Review on Comparison of Different Energy Storage Technologies Used in Micro-Energy Harvesting, WSNs, Low-Cost Microelectronic Devices: Challenges and Recommendations.

The vibration based piezoelectric energy harvester system is considered as an alternative solution for micro-devices, especially for remote area. This paper presents an optimization approach to determine the optimal cantilever beam of a rectangular shape piezoelectric energy harvester to run the micro devices in which power is unavailable. In this study, PZT-5H material has been utilized. The motivation behind this research is to maximize the power behavior by optimizing the cantilever beam’s length, width and thickness. Therefore, the proposed rectangular cantilever beam has been optimized by using modified particle swarm optimization (MPSO) algorithm and designed in COMSOL software. Finally, the optimization results of MPSO are compared with other technique to validate the outcomes. The findings show that the performance of the proposed technique is better than other technique in terms of quality and convergence speed.

An optimization of rectangular shape piezoelectric energy harvesting cantilever beam for micro devices

Current trends of power quality monitoring instruments are based on digital signal processors (DSP), which are used to record waveforms and harmonics and comes with software for collecting data and viewing monitoring results The variations in the DSP based instruments are in the way algorithms that are developed for processing the real-time power quality waveforms At present, all of the available power quality monitoring instruments are not capable of troubleshooting and diagnosing power quality problems Therefore, a DSP-based power quality monitoring instrument is proposed for real-time disturbance recognition and source detection The proposed instrument uses the Texas Instruments TMS320C6711DSP starter kit with a TI ADS8364EVM analog digital converter mounted on the daughter card The instrument architecture and the software implementation are discussed in the paper Preliminary experimental results displaying the fast Fourier transform analysis of the real-time voltage signals are included

Ramizi Mohamed

Papers

PEM fuel cell system control: A review

Artificial Neural Networks Based Optimization Techniques: A Review

Review on Comparison of Different Energy Storage Technologies Used in Micro-Energy Harvesting, WSNs, Low-Cost Microelectronic Devices: Challenges and Recommendations.

An optimization of rectangular shape piezoelectric energy harvesting cantilever beam for micro devices

Development of a DSP-Based Power Quality Monitoring Instrumentfor Real-Time Detection of Power Disturbances