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The paper deals with the design of an active battery charge balancing system for Li-ion batteries. The Li-ion batteries are sensitive to series connection and thus some sort of balancing system must be implemented in battery packs and modules. An active system for batteries balancing based on flyback converter is chosen to deal with this issue. In the first part of the paper a brief presentation of the issue and proposal of system solution is given along with simulation verification. The second part of the paper provides insight into a design together with a hardware and software solutions, mainly focusing on subsystems and initial choice of components. Finally, an experimental verification is conducted for presented design approval.

From the perspective of the space power conditioning unit(PCU) system, this paper studies the battery charging controller based on the Superbuck topology and the characteristics of lithium-ion batteries. We analysis the operating mode of the converter, establish the model of the converter, then we analysis the battery charge control circuit, finally we carry out the simulation and experimental result.

This paper introduces the causes of the capacity decline of lead-acid batteries, and has been converted into practical repair equipment based on the mainstream repair theory and method in the market. The traditional repair equipment is integrated and improved. At present, most of the charger and discharger repair equipment in the market are independent, so no matter from the R & D personnel or ordinary users, the use cost is undoubtedly increased and not convenient. In this paper, the theory of battery charge and discharge and the theory of battery repair are introduced. The theory is transformed into practice, the hardware framework of the system is analyzed, and the circuit design details of each module are analyzed. Finally, the software control flow is analyzed with repair as an example. How to use PWM technology to control the control parameters in repair is analyzed in detail. Finally, the effect of the repair equipment was tested.

This work presents detailed analysis of LLC resonant converter to accurately predcit the voltage gain of the converter. Nowadays, Lithium-ion battery cells are mostly preferred for on-board electrical vehicle (EV) battery chargers due to their high power density. This results in wide range output voltage regulation for battery charger. The output voltage regulation of LLC resonant converter is provided by the changing of switching frequency. However, conventional first harmonic approximation (FHA) method applying for resonant power converters produces error below resonance frequency. Therefore, the objective of this paper is accurate prediction of the voltage gain characteristic for LLC resonant converter using in EV battery charge applications. The detailed theoretical anlysis of the LLC resonant converter is presented and the presented analysis is compared with a simulation study with 2.7 kW output power and 250 V-450 V output voltage range.

The orbital characteristics of low Earth orbit (LEO) satellite systems prevent continuous monitoring because ground access time is limited. For this reason, the development of simulators for predicting satellite states for the entire orbit is required. Power-related prediction is one of the important LEO satellite simulations because it is directly related to the lifespan and mission of the satellite. Accurate predictions of the charge and discharge current of a power system’s battery are essential for fault management design, mission design, and expansion of LEO satellites. However, it is difficult to accurately predict the battery power demand and charging of LEO satellites because they have nonlinear characteristics that depend on the satellite’s attitude, season, orbit, mission, and operating period. Therefore, this paper proposes a novel battery charge and discharge current prediction technique using the bidirectional long short-term memory (Bi-LSTM) model for the development of a LEO satellite power simulator. The prediction performance is demonstrated by applying the proposed technique to the KOM-SAT-3A and KOMSAT-5 satellites operating in real orbits. As a result, the prediction accuracy of the proposed Bi-LSTM shows root mean square error (RMSE) within 2.3 A, and the prediction error well outperforms the most recent the probability-based SARIMA model.

The daily working hours of mobile robots are limited primarily by battery life. Most systems use a combination of thresholds and fixed periods to decide when to charge. This produces charging behaviour that ignores high-value tasks that must be performed within time-windows or by deadlines. Instead the robot should schedule charging adaptively, taking into account the times of day when it is expected to be given more valuable tasks to perform. This paper proposes an approach that exploits the fact that, during long-term deployments, the robot can learn when it is most probable that valuable tasks are added to the system, enabling it to schedule charging at times that are expected to be less busy. We pose the problem of scheduling battery charging as a multi-objective sequential decision making problem over a time-dependent Markov decision process model of expected task rewards and battery dynamics. We evaluate the scalability and solution quality of our multi-objective scheduler, and compare it with a typical rule-based approach. Empirical results show that our approach enables more flexible and efficient robot behaviour, which takes into account both the value of current available tasks and the predicted value of future tasks to decide whether to charge at a given time.

Gelişen teknoloji, sanayileşme ve dünya nüfusundaki artış enerji tüketimini hızla arttırmakta buna paralel olarak fosil yakıtlarının rezervleri süratle tükenmektedir. Fosil enerji kaynaklarının çevre sorunlarına yol açması, rezervlerinin sınırlı ve belirli bölgelerde olması, ülkelerin yenilenebilir enerji kaynaklarına yönelmesine sebep olmuştur. Güneş panellerinin ürettiği enerji atmosferik olaylara bağlı olarak değişkenlik göstermekte olup doğrudan aküyü şarj etmesi uygun değildir. Bu nedenle bu çalışmada şebekeden bağımsız fotovoltaik (PV) sistemlerde kullanılan bataryaların ömrünü artırmak, aşırı şarj ve deşarj olmasının önüne geçmek için Arduino tabanlı şarj kontrol ünitesi tasarlanmış ve uygulaması gerçekleştirilmiştir. Sistem için DA-DA azaltan dönüştürücü Matlab/simulink benzetim programı kullanılarak tasarlanmıştır. Sistemin Ardiuno üzerinden Matlab/simulink ile kapalı çevrim kontrolü oransal-integral (PI) denetleyiciyle gerçekleştirilmiştir. Ayrıca sistem için gerekli olan yazılımsal ve donanımsal aygıtlar başarı ile tasarlanmıştır. Sonuç olarak Arduino tabanlı PI denetimli DA-DA şarj ünitesi benzetim ortamında ve deneysel olarak gerçekleştirilmiş olup elde edilen sonuçlar değerlendirilmiştir., The developing technology, industrialization and the increase in the world population growing up the energy consumption rapidly, in parallel, the reserves of fossil fuels are rapidly depleted. Since fossil energy sources cause environmental problems and their reserves are limited and available in certain regions, countries have been focused on renewable energy sources. The energy produced by solar panels varies depending on atmospheric events. So, it is not possible to charge the battery directly. For this reason, in this study, an Arduino based charge control unit is designed and implemented to increase the life cycle of the batteries used in off-grid photovoltaic (PV) systems and provide overcharge and discharge protection of the battery. The DC/DC buck converter is designed for the system using Matlab/Simulink platform. Closed loop control of the system using Matlab/Simulink program on Ardiuno software development card is carried out with proportional-integral (PI) controller. In addition, software and hardware devices required for the system are designed succesfully. As a result, Arduino based PI controlled DC-DC charging unit is performed in both simulation and experimental set up and the results are discussed.

A novel state estimation algorithm based on the parameters of a self-learning unscented Kalman filter (UKF) with a model parameter identification method based on a collaborative optimization mechanism is proposed in this paper. This algorithm can realize the dynamic self-learning and self-adjustment of the parameters in the UKF algorithm and the automatic optimization setting Sigma points without human participation. In addition, the multi-algorithm collaborative optimization mechanism unifies a variety of algorithms, so that the identification method has the advantages of member algorithms while avoiding the disadvantages of them. We apply the combination algorithm proposed in this paper for state of charge (SoC) estimation of power batteries and compare it with other model parameter identification algorithms and SoC estimation methods. The results showed that the proposed algorithm outperformed the other model parameter identification algorithms in terms of estimation accuracy and robustness.

From the analysis of the operation of electric trains of the ET2, ET2M, ED2T, ED4M, ED4MK series, it was revealed that their failures in some cases are associated with battery failure. The aim of the work is to increase the reliability of the technical condition of the fleet of suburban rail vehicles, by developing and improving scientifically based methods aimed at increasing the life of batteries and control circuits in general. The analysis of charging circuits for rechargeable batteries and power supply of control circuits on electric trains is carried out. A scheme has been developed for stabilizing the charging current of batteries on electric trains. The elements of the circuit of a voltage regulator are calculated and its model is compiled. The analysis of the operation of the circuit based on the transients that accompany the operation of the charger in the process of charging the battery. The analysis confirmed the working ability of the circuit and the correct calculation of its elements. Comprehensive all-season operational tests have confirmed the high efficiency of the developed battery charging circuit eliminating overheating, recharging, and in some cases an explosion, as well as eliminating thermomechanical defects in the control circuits. The developed charging scheme was put into continuous operation on an electric train of the ET2M and ED2T series.

With technological advancement, the automobile industry is undergoing a design evolution. There has been an increase in the use of electrically actuated systems; electronics-based control systems, ...