Variability and intermittency are some of the main features that characterize renewable energy sources. Intermittency usually includes both predictable and unpredictable variations. The many drawbacks of intermittency of renewable sources can be overcome by considering some special design considerations. Integrating more than one renewable energy source and including backup sources and storage systems are among the few measures to overcome these drawbacks. These additional design considerations usually increase the overall cost of the renewable system. Furthermore, the presence of more than one energy supply/storage system requires the control of energy flow among the various sources. Therefore, optimizing the size of the components and adopting an energy management strategy (EMS) are essential to decreasing the cost of the system and limiting its negative effects. The energy management strategy is commonly integrated with optimization to ensure the continuity of load supply and to decrease the cost of energy production. Therefore, energy management is a term that collects all the systematic procedures to control and minimize the quantity and the cost of energy used to provide a certain application with its requirements. The energy management strategy usually depends on the type of energy system and its components. Various approaches and techniques have been used to develop a successful energy management strategy. In this paper, a comprehensive review of the approaches proposed and used by authors of many papers is conducted. These approaches include both the standalone hybrid renewable energy systems and the grid-connected hybrid renewable systems. More attention is focused on popularly used techniques to address the features of each system. The selected papers in this review cover the various configurations of the hybrid renewable energy systems for electric power generation only.

https://scholar.ptuk.edu.ps/bitstream/123456789/89/1/2.pdf

Energy management strategies in hybrid renewable energy systems: A review

In recent years, with the advent of globalization, the world is witnessing a steep rise in its energy consumption. The world is transforming itself into an industrial and knowledge society from an agricultural one which in turn makes the growth, energy intensive resulting in emissions. Energy modeling and energy planning is vital for the future economic prosperity and environmental security. Soft computing techniques such as fuzzy logic, neural networks, genetic algorithms are being adopted in energy modeling to precisely map the energy systems. In this paper, an attempt has been made to review the applications of fuzzy logic based models in renewable energy systems namely solar, wind, bio-energy, micro-grid and hybrid applications. It is found that fuzzy based models are extensively used in recent years for site assessment, for installing of photovoltaic/wind farms, power point tracking in solar photovoltaic/wind, optimization among conflicting criteria. The review indicates that fuzzy based models provide realistic estimates.

Applications of fuzzy logic in renewable energy systems – A review

This article gives an overview of the artificial intelligence (AI) applications for power electronic systems. The three distinctive life-cycle phases, design, control, and maintenance are correlated with one or more tasks to be addressed by AI, including optimization, classification, regression, and data structure exploration. The applications of four categories of AI are discussed, which are expert system, fuzzy logic, metaheuristic method, and machine learning. More than 500 publications have been reviewed to identify the common understandings, practical implementation challenges, and research opportunities in the application of AI for power electronics. This article is accompanied by an Excel file listing the relevant publications for statistical analytics.

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An Overview of Artificial Intelligence Applications for Power Electronics

The rapid consumption of fossil fuel and increased environmental damage caused by it have given a strong impetus to the growth and development of fuel-efficient vehicles. Hybrid electric vehicles (HEVs) have evolved from their inchoate state and are proving to be a promising solution to the serious existential problem posed to the planet earth. Not only do HEVs provide better fuel economy and lower emissions satisfying environmental legislations, but also they dampen the effect of rising fuel prices on consumers. HEVs combine the drive powers of an internal combustion engine and an electrical machine. The main components of HEVs are energy storage system, motor, bidirectional converter and maximum power point trackers (MPPT, in case of solar-powered HEVs). The performance of HEVs greatly depends on these components and its architecture. This paper presents an extensive review on essential components used in HEVs such as their architectures with advantages and disadvantages, choice of bidirectional converter to obtain high efficiency, combining ultracapacitor with battery to extend the battery life, traction motors’ role and their suitability for a particular application. Inclusion of photovoltaic cell in HEVs is a fairly new concept and has been discussed in detail. Various MPPT techniques used for solar-driven HEVs are also discussed in this paper with their suitability.

/pdf/a-comprehensive-review-on-hybrid-electric-vehicles-3pxjmbw5qy.pdf

A comprehensive review on hybrid electric vehicles: architectures and components

In this paper, we propose an adaptive control approach with fuzzy logic parameter tuning (AFLPT) for the energy management of electric vehicles that are using fuel cell battery hybrid systems. The controller is adaptive to different driving conditions including normal, regenerative, and overload conditions. Specifically, the power flow between the fuel cell (FC) and the Li-ion battery is controlled in real time to maintain the battery state of charge (SOC) at a desirable level while satisfying the FC dynamic constraints. For guaranteeing performance in different driving conditions, the FLPT is integrated with the adaptive controller. Moreover, theoretical properties of the designed controller are analyzed. Simulation and experiment results illustrate the effectiveness of the proposed strategy for FC-battery hybrid systems in electric vehicles.

Adaptive Fuzzy Logic Control of Fuel-Cell-Battery Hybrid Systems for Electric Vehicles

To process the power in hybrid energy systems using a reduced part count, researchers have proposed several multiinput dc–dc power converter topologies to transfer power from different input voltage sources to the output. This paper proposes a novel bidirectional nonisolated multi-input converter (MIC) topology for hybrid systems to be used in electric vehicles composed of energy storage systems (ESSs) with different electrical characteristics. The proposed converter has the ability to control the power of ESSs by allowing active power sharing. The voltage levels of utilized ESSs can be higher or lower than the output voltage. The inductors of the converter are connected to a single switch; therefore, the converter requires only one extra active switch for each input, unlike its counterparts, hence resulting in reduced element count. The proposed MIC topology is compared with its counterparts concerning various parameters. It is analyzed in detail, and then, this analysis is validated by simulation and through a 1-kW prototype based on a battery/ultracapacitor hybrid ESS.

A Bidirectional Nonisolated Multi-Input DC–DC Converter for Hybrid Energy Storage Systems in Electric Vehicles

Silicon carbide (SiC) power mosfet s are promising alternatives to Si devices in high-voltage, high-frequency, and high-temperature applications. The rapid and widespread deployment of SiC devices raises long-term reliability concerns, particularly for mission and safety critical systems due to limited field data and potential uncertainties. Therefore, it is essential to investigate progressive degradations and parameter shifts in SiC devices to develop system integrated degradation monitoring tools for self-monitoring converters, which can recognize failure precursors at the earliest stage and prevent catastrophic failures. This paper presents a comprehensive long-term reliability analysis of commercially available SiC mosfet s under high temperature operation and high temperature swing, degradation related key precursors, and possible causes behind them. For this purpose, discrete SiC devices are power cycled and all datasheet parameters are recorded at certain intervals with the aid of the curve tracer. Variation of electrical parameters throughout the tests is presented in order to assess their correlation with the aging/degradation state of the switch. Among them, gate oxide charge trapping related threshold voltage drift and corresponding on state resistance variation has been observed for all samples. For some samples, bond wire heel cracking is found to be the root cause of sudden on state resistance and body diode voltage increases. The discussions regarding aging precursors are supported by failure analysis obtained through the decapsulation of failed devices. Finally, the findings are evaluated in order to define the suitability of electrical parameters as an aging precursor parameter under the light of practical implementation related issues.

Degradation Assessment and Precursor Identification for SiC MOSFETs Under High Temp Cycling

The temperature-sensitive electrical parameters (TSEPs) have been used in silicon carbide (SiC) mosfets junction temperature measurement for over-temperature protection and condition monitoring. However, the device aging can affect the TSEPs and thus leads to false ${\boldsymbol{T}}_{\boldsymbol{j}}$ measurement. In this article, the aging's impacts on various TSEPs are comprehensively investigated. Specifically, utilizing the dc power cycling test, both the gate oxide instability and package degradation are considered. Then the commercial devices with different structures are aged, and their temperature-dependent static and switching characteristics are evaluated at different aging cycles. Both the positive gate bias-induced threshold voltage shift and package degradation are observed, and their impacts on each TSEP are evaluated independently. Based on the evaluation results at various operating conditions, the temperature measurement errors due to different aging mechanisms are well summarized for each TSEP. From the dc power cycling test result, the package degradation's impact on TSEPs is found to be more significant than the gate oxide instability. It is pointed out that the aging's effect on TSEPs is an important factor that needs to be considered for accurate ${\boldsymbol{T}}_{\boldsymbol{j}}$ measurement in SiC mosfets .

Evaluation of Aging's Effect on Temperature-Sensitive Electrical Parameters in SiC mosfets

Experimental performance assessment of an online energy management strategy for varying renewable power production suppression

This paper presents a comprehensive study on degradation monitoring of silicon carbide mosfet s and proposes an early warning method to detect aging. The proposed plug-in tool can be integrated to smart gate drivers or directly to power converters. During the accelerated aging tests (power cycling within safe operating area), several electrical parameters are monitored to find out critical signatures and precursors of failure. Among those, gate leakage current is identified as the most practical precursor, which exhibits consistent changes in all aged devices and is relatively easy to monitor. Due to its simple scheme and low cost, it can potentially be embedded into commercial gate drivers featuring improved reliability options.

Enes Ugur

Papers

A Bidirectional Nonisolated Multi-Input DC–DC Converter for Hybrid Energy Storage Systems in Electric Vehicles

Degradation Assessment and Precursor Identification for SiC MOSFETs Under High Temp Cycling

Evaluation of Aging's Effect on Temperature-Sensitive Electrical Parameters in SiC mosfets

Experimental performance assessment of an online energy management strategy for varying renewable power production suppression

Real-Time Aging Detection of SiC MOSFETs