This paper focuses on the study of the tightly coupled inductive power transfer technology for charging automatic guided vehicles. It highlights how two factors, high-order harmonic currents and variation in self-inductance, affect the system’s efficiency. Due to the low clearance for the automated guided vehicle and the square-wave input voltage, both factors will exert a considerable influence. The presence of harmonics leads to additional power loss, while variations in self-inductance directly affect link efficiency by disrupting resonance conditions. Both factors contribute to a decrease in overall system efficiency. This paper offers an in-depth theoretical modeling of tightly coupled IPT systems, considering the LCC-LCC compensation circuit. It takes into consideration variations in self-inductance and the influence of harmonic currents while maintaining a constant operational frequency. Additionally, the integration of self-inductance variations into the system demonstrates their simultaneous impact on performance alongside harmonic currents. This paper includes finite element analysis (FEM) of the magnetic coupler to illustrate the design process. Furthermore, a simulation with a circular-shaped magnetic coupler, delivering 1.8 kW, is implemented.

Differential power processing (DPP) converters have recently been utilized in solar PV systems to eliminate partial shading losses in series-connected PV modules. A significant advantage of DPP systems over other distributed converters is their relatively small power rating, which is usually a fraction of the rated power of the corresponding PV module. However, selecting the appropriate size for a DPP converter remains a challenge, necessitating a trade-off between converter cost and savings in power losses. Currently, there is no model for accurately determining the required rating for a DPP converter to effectively eliminate power losses. This paper introduces a set of equations for DPP systems connected in a PV-PV architecture, capable of estimating the processed power in DPP converters under any shading scenario. The paper offers a tool for researchers and power electronics to optimally size DPP converter based on the counter shading scenarios. It also highlights key factors influencing the DPP rating. Extensive simulations and verifications are presented to validate the proposed method for determining the optimal size.

Precise estimation of Battery state of charge (SOC) poses a major challenge in managing and operating electric vehicles (EVs). This is mainly due to its complex behaviour that has a nonlinear dependency on parameters like temperature and SOC. Despite the existence of numerous SOC estimation approaches, their accuracy can be enhanced which is crucial for ensuring an optimized energy consumption. This paper aims to increase the SOC estimation accuracy by investigating a neural network aided Kalman filter (KalmanNet), for the first time, to estimate battery SOC in EVs. The obtained results demonstrate lower estimation error compared to well-known conventional filters used for SOC estimation. Specifically, the proposed approach is compared to the extended Kalman filter (EKF) and sigma-point Kalman filter (SPKF).

Partial shading has a negative impact on the extracted power of solar PV systems and significantly reduces the efficiency of solar PV systems. Differential power processing (DPP) architectures have been shown effective in mitigating the power losses and improving the power output through enabling the maximum power point (MPP) operation of each PV module, without the need for processing the entire power output. However, maximum power point tracking is still challenging due to the coupling between converters that causes oscillations resulting in an extracted power reduction. A new MPPT algorithm is proposed in this paper that is fast and able to eliminate the oscillations leading to enhanced power output. The algorithm has the capability to detect the max power level and maintain its operation eliminating the need for continuous perturbation. A comprehensive validation using Simulink is presented which verifies the effectiveness and superiority of the proposed algorithm in comparison to existing approaches. Specifically, the proposed algorithm has faster transient response in addition to improved steady state operation.

Partial shading has a negative impact on a photovoltaics (PV) system and significantly reduces its extracted power and efficiency. Differential power processing (DPP) has shown to be effective in reducing power losses and thus improving the efficiency of partially shaded PV arrays. DPP enables independent maximum power point (MPP) operation of each PV submodule without processing the entire power output lessening the amount of processing power. However, current DPP methods require current and voltage sensors for each DPP converter, in addition to those of the central converter, to achieve MPP operation. These additional sensors increase complexity and implementation cost. To meet this challenge, this paper investigates the possibility of eliminating the DPP sensors and relying only on the already installed sensors of the central converter. A comprehensive validation through Simulink is presented for verification and validation.

Differential power processing converters have been recently used to mitigate mismatch power losses in partially shaded PV modules. They allow series connected PV submodules to operate at their optimal currents enabling the maximum power extraction of each submodule despite receiving dissimilar irradiances. Experimental verifications showed considerable reduction in partial shading power losses due to DPP converters. This paper show that the operation and power extraction of DPP converters can still be improved through model-based approach in comparison to the commonly used heuristic approaches. The proposed model-based approach distinctly finds the optimal current/voltage through models without a heuristic search. The utilized model-based method enhances the transient and steady state performances without a need for an irradiance sensor or additional current/voltage sensors avoiding extra cost or complexity increase.

Partial shading is a serious challenge that negatively impacts the fielded efficiency of solar PV systems. Its effect is larger than proportional to shadowing area and intensity which results in substantial power losses. Differential power processing converters have been utilized recently for almost eliminating partial shading losses. However, they require a large number of DPP converters increasing their complexity and cost and hindering their practicality and commercialization. This paper shows that utilizing the total-cross-tied (TCT) configuration reduces the number of DPP converters by a factor of the number of PV strings. The paper also shows that the configuration does not affect the power output in comparison to that of the existing parallel-series (PS) configuration. The results in the paper are verified through Simulink simulations under variety of shading scenarios.

Ground faults are prevalent in solar PV systems and result in nontrivial power losses that reduce the fielded efficiency of PV systems. They are triggered by unintended connections of PV modules to ground which short-circuit PV modules and wastes their available power. Modeling a PV system with faults using existing tools is time consuming and increases exponentially with system size. This paper proposes a fast-modeling approach for PV systems operating under faults that facilitates predicting and estimating their power losses. The approach does not require simulating the entire I-V curve of PV systems and thus saves significant computational time without scarifying accuracy. The model utilizes Lambert W function that produces an explicit relation between the output current and terminal voltage of a PV system. A Simulink verification is used for validating the comparable accuracy with reduced computational time.

Faults occurring in solar PV systems could subsequently lead to safety hazards and negatively impact reliability and system efficiency. While many fault detection methods exist for fault identification and protection of solar PV systems, recent studies revealed several shortcomings under certain conditions such as partial shading, and low irradiance. This paper investigates faults in PV systems and conducts pattern analysis for changes in PV systems occurring during faults. Several quantities are considered such as changes in power, fault current, and voltage under both homogenous and partial shading conditions at a variety of fault resistances and fault locations. The observed patterns are then exploited to develop a simple approach for detecting faults in PV systems under homogeneous and partial shading conditions. The proposed approach can also differentiate between the occurrence of faults and partial shading. The effectiveness of the method to detect faults has been verified under various atmospheric and partial shading conditions through MATLAB/Simulink simulations.

The highly nonlinear, stochastic nature of photovoltaic (PV) systems impose difficulty in modeling and control design. The controller is employed to efficiently adjust the operating point decided by maximum power point tracking (MPPT) algorithm instead of directly controlling the duty cycle of the DC-DC converters linked to PV system. This paper proposes a linear quadratic regulator (LQR) based tuned PID controller for PV voltage control for a PV system interfaced with a boost converter topology. The proposed model-based controller design is validated through simulation with corresponding stability and robustness check.

Photovoltaic (PV) system characteristics are significantly affected by shading conditions and thus the power productivity of the system is subject to vary accordingly. Therefore, this triggers the need for a broad understanding for the power losses caused by partial shading conditions (PSC). This paper presents an indicative analysis of various kinds of PV power losses associated with different shading scenarios that are likely to take place in real PV system based on MATLAB simulations. Furthermore, to address the impact of bypass diodes implementation, the analysis takes the case of unbypassed PV modules into consideration. The power losses categories are investigated in different PV configurations to highlight the role of system's arrangement and size in power losses associated with partial shading conditions with notable shortcomings and generalizations.

Model-based maximum power point tracking (MPPT) techniques have been developed to improve the tracking transients for PV systems operating under rapidly changing irradiance. Instead of searching heuristically for the maximum power point (MPP), these methods utilize a PV mathematical model to pre-determine the MPP analytically. The irradiance value, required for solving the model, is calculated indirectly using a PV model inverse, as well as the measured current and voltage. Unfortunately, the existing PV model inverse cannot be obtained in a closed form, and thus few simplifications were needed, that affect the accuracy of the irradiance estimation and lead to inaccurate tracking. This paper employs an introduced shunt PV model, distinguished by its ability to provide a closed form inverse, for developing an improved model-based MPPT. The improved accuracy of the irradiance estimation results in an enhanced tracking accuracy and more energy extraction in comparison with the available model based trackers. The effectiveness of the proposed model based MPPT is verified and its effectiveness is evaluated with respect to various existing MPPTs.