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Lithium-ion batteries are commonly used in electric vehicles, embedded systems, and portable devices, including laptops and mobile phones. Electrochemical models are widely used in battery diagnostics and charging/discharging control, considering their high extractability and physical interpretability. Many artificial intelligence charging algorithms also use electrochemical models for to enhance operation efficiency and maintain a higher state of health. However, the parameter identification of electrochemical models is challenging due to the complicated model structure and the high count of physical parameters to be considered. In this manuscript, a comprehensive electrochemical lithium-ion battery model is proposed for the charging and discharging processes. The proposed model accounts for all dynamic characteristics of the battery, including the cell open-circuit voltage, cell voltage, internal battery impedance, charging/discharging current, and temperature. The key novelty of the proposed model is the use of simulated open-circuit voltage and simulated changes in entropy data instead of experimental data to provide battery voltage and temperature profiles during charging and discharging cycles in the development of the final model. An available experimental dataset at NASA for an LCO 18,650 battery was utilized to test the proposed model. The mean absolute error for the simulated charging cell voltage and temperature values were 0.05 V and 0.3 °C, compared with 0.14 V and 0.65 °C for the discharging profile. The simulation results proved the effectiveness and accuracy of the proposed model, while simplicity was the key factor in developing the final model, as shown in the subsequent sections of the manuscript. [ABSTRACT FROM AUTHOR]

In this manuscript, a novel topology is proposed to integrate on-grid and off-grid PV systems supplying the same load premises. The load side is investigated and analyzed, and critical and non-critical loads are separated in terms of power supply. Critical and seasonal loads usually place stress on the grid's point of common coupling (PCC). In the proposed topology, they are supplied by a novel topology for an off-grid solar pump PV system that lacks energy storage integration. The lack of energy storage batteries requires a novel design and sizing scheme for the off-grid PV system, and a methodology is proposed in this manuscript. The on-grid PV system is conventionally designed and coupled with the storage-less off-grid PV system to maintain load supply. The proposed methodology minimizes the ratings of the PCC and hence relieves stress on congested grids with renewable energy penetration, especially in condensed urban areas. The proposed structure enables the operation of microgrids with high penetration levels of renewable energy resources and minimizes dependance on storage batteries for off-grid systems. A case study is presented and thoroughly analyzed with the proposed methodology. The outcomes of the design process are evaluated economically and were found to be feasible, as is detailed and supported with simulation results. [ABSTRACT FROM AUTHOR]

The transport sector is a major consumer of energy, and thus a major contributor to greenhouse gas (GHG) emissions. The introduction of Electric Vehicles (EVs) has helped in mitigating some of the energy demands presented by the transportation system, though the electrical energy still needs to be secured through conventional and renewable resources. Searching for a new power source for vehicles has become necessary, due to incentives and policy initiatives to counter fossil greenhouse gas emissions. This study provides a new efficient Photovoltaic (PV) powered transportation system, which may be utilized instead of traditional public transportation systems. The main idea is to transform the transportation systems used by large campuses into green systems by deploying educated scheduling approaches and utilizing existing renewable energy infrastructures. The German Jordan University (GJU) campus was chosen as a case study. The presented work describes a comprehensive methodology to exploit the full capacity of the existing PV power plant coupled with the rescheduling of the transportation fleet to meet the energy availability and consumption demand. The proposed technique audits the existing renewable energy power plants for optimum operation. The results validate the efficiency of the proposed system and its ability to reduce carbon dioxide (CO2) emissions compared to traditional transportation systems with an acceptable payback period. [ABSTRACT FROM AUTHOR]

This paper proposes a new maximum power point tracking (MPPT) algorithm for thermoelectric generators (TEG). The new-presented method is based on implementing an indirect open circuit voltage detection and short circuit current estimation methods, which will be used to directly control the TEG interface power converter, resulting in reaching the maximum power point (MPP) in minimal number of steps. Two modes of operation are used in the proposed algorithm, namely the perturb and observe (P&O) method for fine-tuning and the transient mode for coarse tracking of the MPP during fast changes that occur to the temperature gradient across the structure. A novel voltage sensing technique as well is proposed in this work, to reduce the number of voltage sensors used to control and monitor the power converter. The proposed strategy employs a novel approach to sense two different voltages using the same voltage sensor. The input and output voltage information is collected from an intermediate point in the converter. The reconstructed voltages are used in the control loops as well as for monitoring the battery output or load voltages. Simulation and experimental results are provided to validate the effectiveness of the proposed algorithm and the sensing technique. [ABSTRACT FROM AUTHOR]