Electric Motor System Research Articles

Desing of an observer with real time monitoring speed and load torque for submersible induction motors

Relevance. When operating submersible equipment for oil production in aggressive environments and transferring wells to the cyclic operation mode, a decrease in the service life of the submersible installation for oil production is observed. In the first case, this is due to the formation of salt deposits and clogging of the working parts of the electric pump with mechanical impurities. In the second case – an increase in the number of starts of the submersible electric motor. To solve the existing problems, it is possible to implement closed control systems for submersible electric motors based on state variable observers, which determines the relevance of the study. Aim. To develop an observer with operational monitoring of the angular velocity of the rotor and the moment of resistance on the shaft of a submersible asynchronous motor at inconsistency of the initial conditions in various operating modes and its testing using modeling tools. Methods. The observer is built on the basis of known engine models in a fixed coordinate system α, β, the theory of IIR-filters to obtain a forecast of estimates of the angular velocity of the rotor and the torque on the shaft and their correction in real time. Results. The authors have proposed the original structure of an observer with operational monitoring of the angular velocity of the rotor and the moment of resistance on the shaft of a submersible asynchronous motor. Conclusions. The paper demonstrates the observer performance with inconsistency of initial conditions and electric motor model data in various operating modes. In all modes, stable estimates of the speed and torque of resistance on the electric motor shaft are obtained. At the same time, the error in estimating the angular velocity under the condition of changing the load on the shaft and starting in the loaded state is no more than 1.2%, which is acceptable in submersible electric motor control systems. It is revealed that the developed observer, under the condition of changing the active resistance of the stator and rotor in the ranges from –25 to +25% of the nominal value, obtains estimates of the angular velocity with an integral error of no more than 5%, except for starting the motor with a decrease in the active resistance of the rotor by 25% of the nominal value –5.53%, which is acceptable in engineering practice.

Electro-thermal co-design of a variable pole toroidal induction motor

The United States Department of Energy targets an 88 % reduction in motor and power electronics volume by the year 2025 while minimizing or eliminating magnet usage. Induction machines are a magnet-free alternative with advantages such as low cost, high reliability, and capability of withstanding high short-term overload. To meet these societal goals, we develop an induction machine that uses an electro-thermal co-designed converter-integrated thermal management approach. The machine utilizes toroidal windings in the stator, and an 18-phase power converter to achieve 40 kW/L power density. An optimized jacket design was developed to enable the effective thermal management of the stator and integrated power electronics. The toroidal winding configuration provides advantages for thermal performance over conventional distributed windings due to an increased winding copper surface area without reducing slot-fill factor, thereby allowing for a higher stator density. The improved thermal performance of the toroidal winding design was verified using three-dimensional conjugate computational fluid dynamic simulations. A reduced-order transient model was then developed to generate torque-speed-temperature plots at various load conditions. The transient thermal analysis was extended to verify safe operation of the motor during a typical drive cycle for the desired application. The thermal design models developed in this work are robust and scalable to other motor sizes providing a framework for co-designing and developing thermal management systems for electric motors.

Enhanced Thermal Modeling of Electric Vehicle Motors Using a Multihead Attention Mechanism

The rapid advancement of electric vehicles (EVs) accentuates the criticality of efficient thermal management systems for electric motors, which are pivotal for performance, reliability, and longevity. Traditional thermal modeling techniques often struggle with the dynamic and complex nature of EV operations, leading to inaccuracies in temperature prediction and management. This study introduces a novel thermal modeling approach that utilizes a multihead attention mechanism, aiming to significantly enhance the prediction accuracy of motor temperature under varying operational conditions. Through meticulous feature engineering and the deployment of advanced data handling techniques, we developed a model that adeptly navigates the intricacies of temperature fluctuations, thereby contributing to the optimization of EV performance and reliability. Our evaluation using a comprehensive dataset encompassing temperature data from 100 electric vehicles illustrates our model’s superior predictive performance, notably improving temperature prediction accuracy.

Comprehensive Multidisciplinary Electric Vehicle Modeling: Investigating the Effect of Vehicle Design on Energy Consumption and Efficiency

In this study, an electric vehicle (EV) dynamic model is devised that amalgamates mechanical design aspects—such as aerodynamic effects, tire friction, and vehicle frontal area—with crucial components of the electrical infrastructure, including the electric motor, power converters, and battery systems. Verification of the model is executed through a comprehensive multidisciplinary analysis utilizing CATIA, ANSYS Electromagnetics, ANSYS Fluent, and MATLAB–Simulink tools, which are applied to evaluate two alternative lightweight EV prototypes. The process involves initial computations of critical inputs for the dynamic model, including aerodynamic lift (C1), drag coefficients (Cd), and frontal area (Af). Subsequent stages entail the detailed design and analysis of a 2 kW brushless permanent magnet electric motor in ANSYS Electromagnetics to map efficiency contours across various speed–torque values. Integration of these parameters into a MATLAB–Simulink dynamic model, connected with motor drive inverter and battery models, allows for simulation-based energy consumption analysis under race track slope profiles. Remarkably, the findings underscore the considerable impact of neglected parameters on energy consumption, often exceeding fifty percent of the total. Consequently, an energy-efficient EV prototype is manufactured and rigorously tested under specified drive conditions, affirming the validation of the comprehensive multidisciplinary EV dynamic model.

A Study Article of Advancing Electric Motor Performance through Maximum Torque Per Ampere (MTPA) Control

Abstract: Electric motor performance can be significantly enhanced through the implementation of Maximum Torque per Ampere control. This advanced control technique allows for optimizing the motor operation by maximizing the torque produced per unit of current. By implementing MTPA control, electric motors can achieve higher efficiency, reduced energy consumption, and improved overall performance. This paper explores the principles and benefits of MTPA control and provides insights into its application across various electric motor systems. The implementation of Maximum Torque per Ampere control has garnered significant attention in the field of electric motor performance enhancement. This advanced control technique offers a promising opportunity to optimize motor operation and achieve higher efficiency. By maximizing the torque produced per unit of current, MTPA control not only reduces energy consumption but also improves the overall performance of electric motors. Furthermore, the application of MTPA control has shown promising results across various electric motor systems, making it a versatile and impactful advancement in the field.

Bi-LSTM predictive control-based efficient energy management system for a fuel cell hybrid electric vehicle

Energy management systems (EMS) in hybrid electric vehicles play a vital role in achieving optimal energy utilization, improved fuel efficiency, lower emissions, and improved vehicle performance. Thus, this paper proposes a Bidirectional Long-Term Memory (Bi-LSTM) model based on an efficient EMS for a hybrid electric vehicle that manages the powertrain elements of the IC engine, electric motor(s), fuel cell, and energy storage system. The proposed EMS also continuously monitors various parameters, including vehicle speed, driver inputs, battery state of charge, engine load, and environmental conditions, to make real-time decisions on power distribution and operation modes. Further, the proposed system leverages the capabilities of the Bi-LSTM model to capture intricate temporal dependencies and bidirectional context in driving patterns using the real-time dataset. Empirical studies are conducted to substantiate the efficacy of the proposed energy management strategy vis-à-vis diverse controllers, encompassing Model Predictive Control and Sliding Mode Control. Real-world driving data is employed as the basis for these investigations, aiming to provide a robust assessment of the proposed energy management approach in practical scenarios. Results demonstrate the efficacy of the suggested methodology compared to traditional EMS approaches, showcasing improvements in energy utilization and reduced environmental impact. Finally, this research emphasizes a comparative analysis of the proposed topology with the existing approaches in a real-world fuel cell hybrid electric vehicle system. The findings provide insights into the feasibility of deploying intelligent EMS strategies for improved sustainability and efficiency in a modern energy-efficient environment.

Optimization of Motor Bracket for Enhanced Performance in Electric Vehicles - A Review

As electric vehicles (EVs) continue to gain prominence in the automotive industry, the demand for efficient and lightweight components becomes crucial for overall vehicle performance. This study focuses on the optimization of the bracket used for mounting the motor in electric vehicles, aiming to enhance structural integrity, reduce weight, and improve overall efficiency. The research employs a multi-faceted approach, combining advanced materials analysis, structural simulations, and manufacturing techniques to achieve an optimal design. Initially, a comprehensive materials selection process is conducted, considering factors such as strength, weight, and cost. Finite Element Analysis (FEA) is then employed to simulate the bracket's structural behavior under various loading conditions, ensuring that it meets stringent performance and safety standards. The optimization process involves fine-tuning the bracket's geometry to strike a balance between weight reduction and structural robustness, thereby improving the overall efficiency of the electric motor system. Additionally, advanced manufacturing methods, such as additive manufacturing and precision machining, are explored to facilitate the production of the optimized bracket. These techniques not only contribute to the reduction of material waste but also allow for complex geometries that further enhance the bracket's performance.

Optimizing Bearing Fault Detection: CNN-LSTM with Attentive TabNet for Electric Motor Systems

Optimizing Bearing Fault Detection: CNN-LSTM with Attentive TabNet for Electric Motor Systems

Enhanced Output Tracking Control for Direct Current Electric Motor Systems Using Bio-Inspired Optimization

In this paper, an efficient output reference trajectory tracking control scheme for direct current electric motor systems based on bio-inspired optimization is proposed. The differential flatness structural property of the electric motor along with dynamic tracking error compensation is suitably exploited for the backstepping control design. Off-line optimal selection of control parameters, implementing bio-inspired ant colony and particle swarm optimization algorithms, is addressed by minimizing an objective function where the decision variables are the tracking error and control input effort. A novel adaptive version of the control approach based on B-spline artificial neural networks is provided as well. The introduced flat output feedback tracking control design approach can be further extended for other differentially flat dynamic systems. Considerably perturbed, diverse velocity and position reference trajectory tracking scenarios are developed for demonstrating the acceptable closed-loop system performance. The results prove the efficient and robust tracking of the position and velocity reference profiles planned for the operation of the controlled electric motor system under variable torque disturbances using bio-inspired optimization.

Estimating Electrical Energy and Capacity Demand for Regional Electric Flight Operations at Two Mid-Size Airports in Washington, U.S

Advances in battery-powered electric motor systems, lightweight materials, and aircraft design have resulted in the development of new battery-electric aircraft that could gradually replace conventional fuel-powered aircraft for certain use cases in the coming years. In the face of tight climate action goals and large airport hubs facing capacity constraints, electric aircraft at regional airports could help respond to increased regional travel demands. Charging these aircraft may be a significant new load on the electric grid serving airports. In this paper, to understand these load impacts, we develop a framework for estimating future energy (annual MWh) and power (average and peak MW) demand for charging battery-electric aircraft at regional airports. We apply our modeling framework to two mid-size case study airports in Washington, U.S: Paine Field/Snohomish County Airport and Grant County International Airport. Our method has three parts: assumptions on flight operations growth, technical feasibility to serve these flights with electric aircraft, and actual adoption of electric aircraft to serve feasible trips. The results reveal that, while electricity demand could rise substantially over time, during the first decade of adoption utility companies are expected to be able to serve the energy and power needs of electric aviation with available capacity at existing substations close to the airports in our case studies.

Recent Developments in Cooling Systems and Cooling Management for Electric Motors

This study provides an overview of new trends in the development of cooling systems for electric motors. It includes a summary of academic research and patents for cooling systems implemented by leading motor manufacturers at TRL9. New trends in the cooling management of air and liquid cooling systems are discussed and analyzed with a focus on temperature distribution and its influence on the power-to-dimension ratio of electric motors. The prevailing cooling method for synchronous and asynchronous motors is air cooling using external fins, air circulation ducts, air gaps, and fan impellers to enhance efficiency and reliability. Internal cooling with rotor and stator ducts, along with optimized air duct geometry, shows potential to increase the power-to-dimension ratio and reduce motor size. Liquid cooling systems offer a power-to-dimension ratio of up to 25 kW/kg, achieved through redesigned cooling ducts, stator heat exchangers, and cooling tubes. However, liquid cooling systems are complex, requiring maintenance and high ingress protection ratings. They are advantageous for providing high power-to-dimension ratios in vehicles and aircraft. Discussions on using different refrigerants to improve efficient motor cooling are underway, with ozone-friendly natural refrigerants like CO2 considered to be promising alternatives to low-pressure refrigerants with high global warming potential.

Reliability Analysis on electric propulsion System Combining GO-FLOW Methodology with Multi-Valued Decision Diagrams

The electric propulsion system of an electric aircraft is the core power of the whole aircraft, which provides assurance for the safe flight of the aircraft. There are multiple stages in the flight process of electric aircraft, as well as different failure behaviors of system components at different stages. The electric motor system is a k-out-of-n system. Therefore, it is not possible to accurately describe the electric motor system with the existing operators when using the GO-FLOW method for electric propulsion system reliability calculations. In order to solve this problem, this paper models the electric motor system using the multi-valued decision diagram method (MDD method), based on which a new operator 43 is proposed to simulate the electric motor system, and then builds the GO-FLOW model and calculates the overall reliability based on the distributed electric propulsion system schematic. The example results show that the method can calculate the reliability of the distributed electric propulsion system more realistically.

Quick Electrical Drive Selection Method for Bus Retrofitting

The article concerns the issue of retrofitting (i.e., the conversion of worn-out diesel buses into electric buses). As this solution is often cheaper than purchasing new electric buses, it can be attractive for low-population areas with a weaker economic infrastructure. The article aims to present an original method for rapidly selecting components for the electric traction system, such as the electric motor, inverter, and transmission systems, combined with a battery installed in a drawer. The battery swapping solution is dedicated to regions with underdeveloped power infrastructure that does not allow for fast charging of bus batteries using pantographs. A mathematical model in the form of a polynomial was developed to estimate the energy losses for a given route. This model consists of a bus physics model, an energy loss model in the propulsion system, and a battery model. The weight coefficients of the polynomials were determined based on an analytical analysis of the model dependencies. The obtained models were reduced using the Lasso regularization method in linear regression. The input data for the model includes route characteristics (or driving cycle) and technical characteristics of the traction system components. The model output provides a detailed profile of electric energy consumption and peak values of the drive system characteristics (e.g., maximum torque of the motor) which must not be exceeded. Implemented as computer software, the model—combined with a database of motors, inverters, drive transmission systems, and batteries—allows for a quick calculation of the possibilities of applying a selected configuration to cover a given route. The approach proposed in the article enables the rapid composition of electric traction devices based on required driving conditions during the initial vehicle prototyping stage. At the same time, it allows the state of the bus battery to be monitored and estimates the remaining range during the operation of upgraded buses.

Research on and Design of an Electric Drive Automatic Control System for Mine Belt Conveyors

Conveyor belts are widely used in ore transportation in large-scale mines for their long transportation range, high safety, and strong economic applicability. Coal mine belt conveyors are not only traditional, simple mechanical conveying devices but also automatic control system operating devices that integrate safety, stability, and low power consumption. In the process of coal mining, a conveyor belt control system also needs to be closely integrated with modern industrial systems and information systems, which greatly improves its work efficiency. The purpose of this article is to improve the methods for designing automatic control systems for electric motors in order to obtain mechanical characteristics close to a constant power line, which would ensure the reliable operation of belt conveyors. An automatic control system was designed based on the controller Siemens S7-1200; then, a mathematical model of an automated electric drive was developed. Based on the mathematical model, a simulation model of an automatic electric drive was built, and the modes were modeled. After designing, the obtained plots of transients completely corresponded to the required transients, which means that the Siemens frequency converter automatic control system (ACS) parameters were calculated quite accurately and the conveyor electric drive met all requirements.

Measures to increase the technical resource of electrical equipment of powerful irrigation pump stations

RELEVANCE. At present, unstressed systems for launching high-voltage electric motors have been increasingly used. These systems limit the values of starting currents as well as eliminate alternating oscillations of engine electromagnetic torque. THE PURPOSE. Development of measures to improve the technical resource of electrical equipment of powerful irrigation pumping stations based on the use of soft start systems for high-voltage electric motors. METHODS. In the course of the study, methods for analyzing the technological processes of a pumping station, methods for mathematical and computer modeling of an electric drive were used. RESULTS. Computer models have been developed to study the regime characteristics of asynchronous and synchronous electric drives of pumping stations with direct and soft start of electric motors. A shockless start-up system for high-voltage electric motors of irrigation pumping stations of the first lift based on a current inverter is proposed. CONCLUSION. The reliability and durability of electrical equipment depends primarily on the technical resource, which is determined by a number of factors. The main factors influencing the technical life of the electrical equipment of large irrigation pumping stations are the transient modes that occur when the pumping units are started. The soft start system of high-voltage electric motors of irrigation pumping stations proposed in this article makes it possible to eliminate the negative impact of transient conditions on the operation of electrical equipment and, thereby, increase the technical resource and reliability of the power supply system of the pumping station as a whole.

Economic Analysis of Variable Speed Drive Control Through Profinet Technology on Distributed Control System: A Case Study in Essential Oil Processing Factories

Electrical equipment in essential oil processing plants is generally dominated by electric motor loads. In today's digital era, global competition and technological advances encourage factories to increase the efficiency and reliability of their production equipment. One way of efficiency is to use a variable speed drive (VSD). The existence of Profinet technology as a network protocol between the control equipment and the VSD allows users to increase system reliability while increasing energy use efficiency. Even so, there are still many factories that are hesitant to use this technology in their automation systems. Many low to medium-sized factories still use traditional control methods such as hardwired. This method is considered more reliable, and inexpensive compared to using Profinet technology. Cost-benefit analysis is carried out to prove this paradigm. At the same time provides certainty that the investment costs incurred in building the system provide added value for production equipment. From this research, it is proven that the use of Profinet technology in addition to providing savings on investment costs also provides benefits from a technical perspective. This technology also allows the implementation of condition-based monitoring systems for electric motors in production equipment. Which in turn can increase the performance and service life of the machine.

Design and Modeling of Hybrid Electric Vehicle Powered by Solar and Fuel Cell Energy with Quadratic Buck/Boost Converter

Considering technological advancements and international standards mandating reduced greenhouse gas emissions, automobile manufacturers have shifted their focus toward innovative technologies related to fuel-cell electric vehicles. Despite having an all-electric powertrain, fuel cell electric vehicles (FCEVs) utilize a fuel cell stack as their energy source, which runs on hydrogen and results in the emission of only water and heat. Due to the absence of tailpipe pollutants, fuel-cell electric vehicles are considered zero-emission vehicles. Among fuel cell types, low-temperature and low-pressure fuel cells, such as Proton Exchange Membrane Fuel Cells (PEMFCs), are well-suited for vehicular applications as they exhibit high power density, operate at lower temperatures (60-80°C), and are less prone to corrosion than other types of fuel cells. The main objective of this paper is to investigate solar-assisted electric fuel cell vehicles that efficiently integrate the fuel cell system with an electrolyzer and solar power to fulfill the fluctuating power demands of the electric motor and auxiliary systems. A novel EV configuration with a fuel cell, electrolyzer and onboard PV cell is proposed. An onboard PV cell can assist the fuel cell when the irradiation is enough to generate the power. During the idle conditions of vehicles, PV-generated power can be converted into chemical energy using an electrolyzer and generated hydrogen can be stored in a hydrogen tank. To match the voltage required by the motor and sources a quadratic bidirectional buck-boost converter is employed. The proposed configuration is examined by considering variable irradiance and variable speed values. To obtain the maximum power output from the photovoltaic (PV) panel, a Maximum Power Point Tracking (MPPT) algorithm is employed to regulate the PV system. To enhance the efficiency and cost-effectiveness of PV systems, an enhanced version of the incremental conductance algorithm is utilized as the MPPT control strategy. Outer voltage and inner current control are adopted to regulate the DC output voltage of the QBBC converter. An indirect vector-controlled induction motor is used as vehicle drive. Simulations are performed to investigate the proposed EV configuration in MATLAB/SIMULINK.

고장진단을 위한 영구자석형 동기모터 유한요소 모델 개발

This paper proposes a high-fidelity finite element model of a permanent synchronous motor (PMSM) to predict electromagnetic responses. The proposed method aims to generate electromagnetic responses from the PMSM under various operational conditions-including normal and faulty conditions-by coupling several partial differential equations governing the electromagnetics of a PMSM. The rotor eccentricity is considered to be a representative fault of a PMSM, which has electromagnetic characteristics that differ from the healthy state of a PMSM. Note that eccentricity is the most frequent fault during PMSM operation. Therefore, the proposed model could replicate the defected torque responses of an actual motor system. The effectiveness of the proposed model is validated using measurements from a PMSM test bench. Quantitative comparison reveals that the proposed model could replicate both the transient- and steady-state torque responses of the PMSM of interest at a variety of operational conditions, including a faulty status. The proposed model could be used to generate virtual electromagnetic responses of a PMSM, which could be used for data-driven fault detection methods of electric motor systems.

An Unmanned Helicopter Energy Consumption Analysis

The number of operations incorporating E-VTOL aircrafts is increasing each year, and the optimization of the energy consumption of such vehicles is a major problem. In this paper, a small-scale ARCHER helicopter’s energy consumption is analyzed, wherein different flight conditions, main rotor revolutions, and flight control system settings are considered. The helicopter dynamic model was developed in the FLIGHTLAB environment and was then validated based on flight test data. The model used for the calculation of energy consumption was developed using the electric and dynamic characteristics of the main rotor, electric motor, and transmission system. The main part of this work concerns the analysis of electric energy consumption during the vehicle’s flight via the use of an automatic flight control system (AFCS) that ensures repeatable flight conditions. The AFCS was designed such that it includes both path and attitude control to provide hover and cruise control modes. The helicopter’s energy consumption was analyzed during different phases of flight, when executing maneuvers, and using different main rotor angular velocities to perform - a given task. The results show that the level of energy consumption significantly depends on the helicopter’s main rotor revolutions, flight speed, and the maneuvers performed. The proposed methodology can be used in prospective energy-efficient mission planning and UAV helicopter design.

A Model Predictive Control Approach for Electro-Hydraulic Braking by Wire

In this article, based on a novel electro-hydraulic braking system for full self-driving vehicles, a model predictive control approach is designed for precisely tracking of braking pressure. Concerning electric motor, reduction mechanism, and hydraulic system, a new braking system model is formulated. Due to the nonlinear hydraulic characteristic of the master cylinder piston, a quadratic polynomial is utilized to fit a relationship between piston position and cylinder pressure, by which a desired pressure of master cylinder is transformed into a desired position of the piston. A recursive least square with forgetting factor is developed to find the optimal parameters of pressure–position relationship. A system friction model is established to calculate the equivalent friction torque, which is regarded as the compensation of the desired torque. A vehicle test bench of full self-driving is established to validate the designed approach. According to the accurate tracking and the quick response of braking pressure from experimental results, it can be concluded that the model predictive control approach is a good candidate for the pressure demand control of electro-hydraulic braking by wire.