Electrical Research Articles

Deep learning-based electric vehicle transmission system speed ratio prediction research

Deep learning-based electric vehicle transmission system speed ratio prediction research

A Review on Towards Long Lifetime Battery: AI Based Manufacturing and Management

A Battery Management System (BMS) is crucial for maintaining the health and efficiency of batterypowered devices. Integrating Artificial Intelligence (AI) into BMS offers advanced capabilities for optimizing battery performance. AI algorithms analyze real-time data from the battery, such as voltage, temperature, and charge cycles, to predict battery life, enhance safety, and improve energy efficiency.AI can detect patterns and anomalies that traditional systems might miss, allowing for proactive adjustments to charging and discharging processes. This helps prevent overcharging, overheating, and deep discharges, which can damage batteries and reduce their lifespan. Additionally, AIdriven BMS can learn from historical data to refine its predictions and adapt to changing conditions. It also supports better energy management in electric vehicles and renewable energy systems, where efficient battery use is critical. By continuously monitoring and optimizing battery performance, AI enhances the overall reliability and longevity of battery systems, making technology more sustainable and efficient. Thus, the use of AI in BMS represents a significant advancement in battery technology, contributing to improved performance and safety in various applications. This study explores battery management systems by optimizing performance, extending lifespan, and improving efficiency and ensure safety through predictive analysis and real-time monitoring. Keywords: Battery Management system, artificial intelligence, state of charge, state of health, battery life extension, fault detection.

Experimental study on performance of 100kW low temperature superconducting steady-state magnetoplasmadynamic thruster

Abstract Applied field magnetoplasmadynamic thrusters (AF-MPDTs), with their high specific impulse and considerable thrust, are increasingly favored for large-scale space missions. This paper presents the composition, functionality, and testing methods of a high-power electric propulsion performance testing system, along with the vacuum ignition test results of a 100 kW superconducting MPD thruster. The relationships between thruster effciency, magnetic field strength, current, and mass flow rate are analyzed. For each combination of current and flow rate in an AF-MPDT, there is an optimal magnetic field strength where the thruster effciency reaches its peak. Under conditions of 320 A current and 60 mg/s flow rate, the optimal magnetic field strength is 0.5 T, yielding the highest thruster effciency of 71%.

A Model-Driven Approach for Estimating the Energy Performance of an Electric Vehicle Used as a Taxi in an Intermediate Andean City

Regarding the decision to opt for vehicles with electric propulsion systems to achieve a sustainable future, much research has focused on the electrification of passenger cars, since this class of vehicles is the largest contributor of greenhouse gas emissions in the transportation sector. The purpose of this paper is to assess the energy performance of an electric vehicle used as a taxi in Loja, Ecuador, an intermediate Andean city, using a model-driven approach. Data acquisition was performed through the OBDII port of the KIA SOUL EV for 24 days and the variable mass of the vehicle was recorded as a function of the number of passengers; the effects of road gradient were also considered. The energy performance of the vehicle was simulated by developing an analytical model in MATLAB/Simulink. An average measured battery performance of 8.49 ± 1.4 km/kWh per day was obtained, where the actual energy regenerated was 31.2 ± 1.5%. To validate the proposed model, the results of the daily energy performance estimated with the simulation were compared with those measured in real driving conditions. The results demonstrated a Pearson correlation coefficient of 0.93, indicating a strong positive linear dependence between the variables. In addition, a coefficient of determination of 0.86 and a mean absolute percentage error of 3.35% were obtained, suggesting that the model has a satisfactory predictive capacity for energy performance.

Analysis of the Effectiveness of Using Active Filters and Passive Filters in Reducing Harmonics Using a Power Simulator (PSIM) at PT. Delta Jaya Mas

The Extruder Machine at PT. Delta Jaya Mas plays a critical role in the production of rubber and PVC hoses, as well as molded rubber products. This process involves the use of a 3-phase synchronous motor and Variable Frequency Drive (VFD), which can introduce harmonics into the electrical system due to their non-linear load. These harmonics can cause waveform distortion, leading to decreased efficiency and potential equipment damage. To overcome this issue, a comprehensive research is being conducted utilizing the Power Simulator (PSIM) program to analyze the impact of harmonics and evaluate the effectiveness of both active and passive filters in reducing these unwanted distortions. Initial assessments of the Extruder SDP panel revealed elevated levels of Total Harmonic Distortion (THD) in the current phases, while the voltage phases remained within acceptable thresholds. Simulation results demonstrated that the active filter was able to significantly reduce THD to an impressive 1.57%, showcasing its effectiveness in harmonic mitigation. On the other hand, the passive filter also proved beneficial, albeit to a slightly lesser extent, achieving a reduction in THD to 34.07%. This ongoing research not only aims to assist PT. Delta Jaya Mas in implementing appropriate harmonic reduction measures for their Extruder Machine but also seeks to advance the understanding of harmonic analysis and filter applications.

Review on electrical submersible pump failures detection and monitoring system

Review on electrical submersible pump failures detection and monitoring system

Detection of High Resistance Contacts in the Electrical Distribution System During the Induction Motor Starting Transient

Detection of High Resistance Contacts in the Electrical Distribution System During the Induction Motor Starting Transient

Control Design of Fractional Multivariable Grey Model-Based Fast Terminal Attractor for High Efficiency Pure Sine Wave Inverters in Electric Vehicles

In this paper, a fast and efficient control method is proposed for a pure sine wave inverter used in an electric vehicle system, which can provide better performance under transient and steady-state conditions. The proposed control technique consists of a fast terminal attractor (FTA) and a fractional multivariable grey model (FMGM). The FTA with finite time convergence offers a faster convergence rate of the system state and a singularity-free solution. However, if the uncertain system boundaries are overestimated or underestimated, chatter/steady-state errors can occur during the FTA, which can lead to significant harmonic distortion at the output of the pure sine wave inverter. A computationally efficient FMGM is incorporated into the FTA to solve the chatter/steady-state error problem when an uncertain estimate of the system boundary cannot be satisfied. Simulation results show that the proposed control technique exhibits low total harmonic distortion. Experimental results of a prototype pure sine wave inverter are presented to support the results of the simulation and mathematical analysis. Since the proposed pure sine wave inverter outperforms the classical TA (terminal attractor)-controlled pure sine wave inverter in terms of convergence speed, computational efficiency, and harmonic distortion elimination, this paper will serve as a useful reference for electric vehicle systems.

Investigation of Electric Field Coupling Wireless Power Transfer System with Immittance Converters

Investigation of Electric Field Coupling Wireless Power Transfer System with Immittance Converters

Influence of the use of ground enhancement materials on the reduction of electrical resistivity in grounding systems: a review

A grounding system (GS) is an indispensable component in an electrical system network, as it is responsible for conducting electrical discharges to the ground due to faults caused by lightning strikes or transient system failures. Globally, it is estimated that 40 lightning strikes occur per second on the planet, amounting to around 1.2 billion per year, resulting in daily losses of various electrical equipment and human fatalities ranging from 6,000 to 24,000. Additionally, soil resistivity, which impedes the flow of electricity from electrical discharges into the ground, leads to inadequate mitigation of electrical overload effects, resulting in poor GS performance. Consequently, the implementation of ground enhancement materials (GEMs) to reduce impedance to optimal levels becomes necessary. The objective of this review is to broadly examine the current status of GEMs reported in the literature for use in GS, focusing on their composition and their effectiveness in improving soil conductivity and dissipating electrical currents as well as to identify emerging trends and current challenges in the development and application of these materials, in order to provide information to guide future research in the design and implementation of efficient and safe GS.

A Hybrid Optimization Algorithm Based on Cascaded (1+PI)-PI-PID Controller for Load Frequency Control in Interconnected Power Systems

Electric power generation is crucial for electrical systems, and load frequency control (LFC) ensures system synchronization and reliability. Modern systems use well-designed controllers, with selecting the right type and design approach being essential for a good LFC controller design. This study introduces a cascaded (1+PI)-PI-PID controller optimized using the improved Artificial Bee Colony-Particle Swarm Optimization (IABC-PSO) algorithm for LFC in interconnected power systems, aiming to address complex challenges associated with LFC in modern power systems. The research examines a two-area power system model with hydro and thermal power plants and a capacitive energy storage (CES) device. It proposes a (1+PI)-PI-PID controller structure that integrates traditional PID controllers, enhancing performance and debugging capabilities. The study uses integral absolute error (IAE), integral square error (ISE), integral time absolute error (ITAE), and integral time square error (ITSE) as objective functions. The IABC-PSO algorithm introduces a novel decision block to increase scout bee (SB) occurrences to 10% for each employed bee (EB), and a new control search phase to optimize SBs' exploration capabilities in a controlled manner, enhancing their efficiency. The algorithm's performance was assessed using four benchmark functions, revealing superior results compared to the Hybrid ABC-PSO algorithm. The study examined six experimental configurations of the controller, varying the sequence of (1+PI), PI, and PID components. The proposed strategy was tested under 1% and 5% step load perturbations in area-1 and area-2 to evaluate dynamic performance. This study conducts a sensitivity analysis by adjusting hydro parameters within a ±25% range, and considers generation rate constraint (GRC) and boiler dynamics (BD) in a two-area reheat thermal-hydro-power system model for reliability and credibility. The proposed IABC-PSO algorithm outperforms traditional methods (ABC, PSO, and hybrid ABC-PSO, WOAw, GWO, hSFS-LUS, and FA) in optimizing parameters, achieving shortest settling times and minimal ITAE values. Its performance is evaluated under random step load perturbations (SLP) and its internal robustness is demonstrated through stability analysis using the Lyapunov method. In conclusion, the hybrid IABC-PSO algorithm-based cascaded (1+PI)-PI-PID controller offers a robust and efficient solution for LFC in interconnected power systems. It ensures enhanced performance, stability, and adaptability, making it a valuable contribution to modern power system management.

Capital budgeting for electrical engineering projects: A practical methodology

The paper presents the capital budgeting process and identifies key elements in the process. A standardized approach in capital budgeting by application of information technology resources for both proposal submission and documentation becomes key to success in handling large volumes. An electrical engineering distribution system design project involves the application of engineering codes and standards to stay compliant and provide safe design and construction. A model starting with proposals acceptance to evaluation and approval of capital projects was presented. The proposal stage was decoded further into assessments of the existing electrical infrastructure based on aging and engineering standards. Upon review of the standards, the proposals were accepted for evaluation and approval. For business professionals, there is a gap when working in an electrical engineering construction industry when it comes to knowing applicable engineering standards and their application. This research filled that gap by enlisting the intent of the standards review process. Although the focus was on understanding a holistic approach to electrical engineering projects, a detailed analysis of specific tasks may be designed based on the model presented in this paper. Additionally, the transmission side of projects will have a similar application of capital budgeting.

Comparative Analysis of Marine Alternative Fuels for Offshore Supply Vessels

This paper provides an in-depth analysis of alternative fuels, including liquefied natural gas (LNG), hydrogen, ammonia, and biofuels, assessing their feasibility based on operational requirements, availability, safety concerns, and the infrastructure needed for large-scale adoption. Moreover, it examines hybrid and fully electric propulsion systems, considering advancements in battery technology and the integration of renewable energy sources, such as wind and solar power, to further reduce SOV emissions. Key findings from this research indicate that LNG serves as a viable short- to medium-term solution for reducing GHG emissions in the SOV sector, due to its relatively lower carbon content compared to MDO and HFO. This paper finally insists that while LNG presents an immediate opportunity for emission reduction in the SOV sector, a combination of hydrogen, ammonia, and hybrid propulsion systems will be necessary to meet long-term decarbonisation goals. The findings underscore the importance of coordinated industry efforts, technological innovation, and supportive regulatory frameworks to overcome the technical, economic, and infrastructural challenges associated with decarbonising the maritime industry.

Preparation and performance study of self-repairing coating with superhydrophobic properties

Electricity has become one of the most important energy sources required for the operation of today’s society, and related electrical facilities are constantly being constructed. However, the environment in which electrical facilities are located is complex, how to protect their key components from corrosion has become an urgent problem to be solved. In this study, a kind of superhydrophobic coating with self-repairing properties was prepared based on polycarbonate polyurethane, which can be used to some extent as an anti-corrosion coating in electrical systems. A series of polyurethanes were prepared by adjusting the ratio of various crosslinkers, and the formula that can produce the best comprehensive performance was determined. Specifically, due to the action of disulfide bonds and hydrogen bonds, the prepared polyurethane can achieve a maximum fracture strength of 7.99 MPa and a fracture elongation of 749.19 %, while also having a self-repairing efficiency of 90.86 %. By spraying modified SiO2 to the surface, the polyurethane surface has excellent superhydrophobic properties, with a maximum WCA of 169.67°, and still maintains superhydrophobic properties after being worn for 2100 cm by 800 mesh sandpaper. And the coating also has excellent anti-corrosion property with protecting Q235 metal steel from corrosion in NSS test for 120 h. It has shown great potential in the anti-corrosion application of metal materials in electrical systems.

Two-Layer Optimization Scheduling of Electric Vehicle Charging and Energy Storage Systems in Microgrids

Two-Layer Optimization Scheduling of Electric Vehicle Charging and Energy Storage Systems in Microgrids

Optimization of charging infrastructure and strategy for an electrified public transportation system

Government policies and incentives aimed at reducing the carbon footprint are increasingly focusing on the electrification of public transportation, particularly transit buses. However, electrification faces significant challenges, including optimizing the charging infrastructure, battery size and type, and charging strategies. Addressing these challenges is crucial for the effective deployment and operation of electric bus fleets. This study presents an innovative method for optimizing these aspects of electric bus systems under diverse route conditions. By leveraging general transit feed specification (GTFS) and GeoTIFF data, the developed approach ensures scalability and is grounded in real-world data. A detailed physical model, especially concerning battery degradation, adds a unique dimension to the study, providing more accurate and reliable results. The optimization method employed in this study is dynamic programming (DP), which allows for a comprehensive evaluation of various factors influencing the performance and efficiency of electric buses. The proposed approach has been validated through three distinct case studies. The findings of this study indicate that the optimized solution can lead to a substantial cost reduction of nearly 35% for operators compared to current state-of-the-art practices in Zurich, which underscores the potential of the proposed approach to contribute to more sustainable and cost-effective public transportation systems.

Clinical trial to verify the safety of an automatic electric airway suction system: a multicenter prospective randomized study

BackgroundAcute lung injury and respiratory failure in patients in the intensive care unit (ICU) present challenges owing to varied factors. Manual suctioning, which is the current standard, burdens healthcare professionals and poses risks. The Lmeca.A1000 automatic suction device offers an innovative solution to this problem. This study aimed to evaluate the safety of this device.MethodsThis prospective, multicenter, randomized trial compared automatic and manual suction in ICU patients. Mucosal injury and pneumonia were assessed using bronchoscopy and monitoring. Mechanical stability and adverse events were also evaluated.ResultsIn total, 117 critically ill adults were screened: 56 in the experimental group and 53 in the control group completing the study. No significant difference in mucosal injury was found at 3 or 7 days after treatment (p = 0.871, and 0.750). The incidence of VAP over 2 weeks was 5.36% in the experimental group and 1.89% in the control group, not significantly different (p = 0.582). Adverse events occurred in 14.3 and 13.2%, respectively, with no significant difference (p = 0.870). The incidence of clinical trial device malfunction within 3 days of application was 0.03% and within 2 weeks of follow-up was 0.02%.ConclusionsThis study evidenced the non-inferiority of the automatic suction device to the manual method in terms of safety. The adoption of an automated system could alleviate the workload of healthcare professionals while maintaining effective airway management.

Holistic approach to energy storage management aspects in sustainable community

Energy management is nowadays key topic for synchronic operation of renewable sources of energy and their recipients. Contemporary national electrical power grid systems more often cannot supply efficiently electrical energy and cannot receive energy produced by renewable sources. The common approach to the problem is to meet energy demands supplying from electrical grid and renewable power sources with energy storage feature. From the other side, off-grid solutions based on the co-generation biogas plants are commonly aimed on small local communities as power supply supported by renewable energy systems like photovoltaic (PV) systems, wind power plants or small water plants with energy storage to support self-consumption of electrical energy. Integration of intermittent renewable power sources, such as solar, wind and biogas plant, increases the difficulty of managing the electricity grid and maintaining the balance of electricity supply and demand, especially in small communities. The holistic approach to the energy storage management takes all above aspects and presents the concept where municipal waste is used to produce energy in biogas plant supported by PV systems and community shared electrical energy storage to provide uninterrupted power supply. The study also presents how energy storage management can be used in whole process to adjust the size and manage energy supply and demand within the community based on energy self-consumption optimization. It is also shown that by utilizing municipal waste produced by the community we can meet the goals of circular economy and sustainable development of local communities as the waste will be used in full without necessity of recycling it outside the community. The novelty of the study is the foundation for energy storage capacity and renewable energy sources size evaluation to balance energy management process without the need of on-grid power supply and with use only municipal biodegradable waste for biogas fuel supply and solar energy for energy production.

Real-Time Short-Circuit Current Calculation in Electrical Distribution Systems Considering the Uncertainty of Renewable Resources and Electricity Loads

Existing short-circuit calculation methods for distribution networks with renewable energy sources ignore the fluctuation of renewable sources and cannot reflect the impact of renewable sources and load changes on short-circuit current in real time at all times of the day and in extreme scenarios. A real-time short-circuit current calculation method is proposed to take into account the stochastic nature of distributed generators (DGs) and electricity loads. Firstly, the continuous power flow of distribution networks is calculated based on the real-time renewable energy output and electricity loads. And then, equivalent DG models with low-voltage ride through (LVRT) strategies are substituted into the iterative calculation method to obtain the short-circuit currents of all main branches in real time. The effects of different renewable energy output curves on distribution network short-circuit currents are quantitatively analyzed during the fluctuation in distributed power output, which can provide an important basis for the setting calculation of distribution network relay protection and the study of new principles of protection.

A Review of Harmonic Detection, Suppression, Aggregation, and Estimation Techniques

The rapid growth of power electronics-based devices, such as electric vehicles and renewable energy systems, has introduced nonlinear components into power systems, generating high-frequency harmonics that distort current and voltage waveforms. These distortions pose significant risks to the stability of power grids, potentially leading to equipment malfunctions, reduced efficiency, and even system failures. To address these challenges, advanced harmonic detection, suppression, and estimation techniques are required to ensure the reliable operation of modern power systems. This paper comprehensively reviews the most widely used methods for managing harmonic distortions, focusing on recent harmonic detection, suppression, and estimation advancements. Key techniques, such as Fourier analysis and wavelet transforms, are compared alongside emerging machine learning-based approaches and adaptive filtering methods, which offer enhanced accuracy in real-time and dynamic environments. Additionally, advancements in harmonic suppression technologies, including passive, active, and hybrid filtering, are discussed for their effectiveness in mitigating harmonic impacts. Furthermore, the paper explores harmonic aggregation techniques that assess the cumulative impact of multiple harmonic sources and innovative estimation models that improve harmonic quantification under complex grid conditions. With the growing integration of renewable energy and electric vehicles, this review highlights the importance of advanced harmonic management strategies to ensure the safety, efficiency, and long-term stability of power systems.