The main role of a designer of electrical application is to determine each dimension so that it meets requirements.
To determine the best design parameters set, it is desirable to be able to change each dimension as much as possible while still maintaining the shape.
By using the automatic geometric constraints included in JMAG, anyone can easily set such constraints.
When dealing with extremely complex shapes, automatic constraints may not be fully constrained or dimensions may not be able to be changed significantly.
However, with some ingenuity, it is possible to make shape changes suitable for parametric analysis.
This poster will demonstrate how to use automatic geometric constraints and the workflow for performing parametric analysis and optimization.
It will also explain ingenuity and solutions when dealing with complex shapes.

In device design, the need to meet increasingly complex requirements while shortening development time has made early-stage design evaluation more important than ever.
Traditionally, designers have optimized a limited number of candidate models individually.
However, to reliably identify designs that meet requirements, it is essential to explore a broader design space and evaluate multiple options.
JMAG supports this process through the use of simulation databases and Design Explorer.
By consolidating design data from various machine types into a single database, and applying filtering, comparison, and analysis, engineers can evaluate design candidates from multiple perspectives.
This poster introduces how to use Design Explorer in combination with simulation databases to support early-stage design space exploration and evaluation.

In the design of high-efficiency motors, it is required to simultaneously meet multifaceted requirements such as magnetic performance, temperature, stress, insulation, and vibration.
This poster introduces an optimization design methodology through simultaneous multifaceted evaluation, including thermal and vibration analyses, using JMAG for permanent magnet motor analysis cases.
We explain a practical approach to a design workflow that moves beyond the conventional magnetics-centered design approach, reducing the risk of rework while balancing performance, reliability, and cost.

We have been developing and improving JMAG-Express as a motor design tool, and over the past year we have significantly enhanced its performance and visibility.
Specific improvements include zooming in when selecting rotors and stators, reorganizing design table items, adding graphs for current torque characteristics (I-T characteristics) and phase voltage characteristics (β-V characteristics), highlighting dimensions when setting optimization and using response values for dependent dimension variables.
This has made it an easy-to-use tool that also allows for smooth multi-disciplinary evaluation and optimization.
This poster will explain the improvements made to the latest version of JMAG-Express and introduce a case study of multi-disciplinary evaluation and optimization.

In recent years, topology optimization has attracted attention as a means of exploring innovative shapes for electrical devices without being constrained by conventional design know-how. It is increasingly being adopted in applications such as motors and induction heating.
On the other hand, in actual equipment design, there are parameters that should be treated as real values, such as the number of turns, current values, and magnet orientation. By performing optimization that considers both topology and these parameters (hybrid optimization),
the search space can be expanded, leading to further advancement of the Pareto front.
This poster presents the exploration results of hybrid optimization solutions, along with the computational environment and computation time, and discusses their usefulness.

-A case study where the magnet shape of an SPM motor is treated as topology and the magnet orientation as a parameter
-A case study where the coil shape for induction heating is treated as topology and the current value and frequency as parameters
-A case study where the core shape of a power reactor is treated as topology and the number of turns and coil region dimensions as parameters

To develop higher-performance electrical devices, optimization techniques that explore the design space broadly to find feasible designs are gaining attention.
In electrical device design, the design space is composed of not only continuously changing variables such as dimensions of device geometry, but also discrete variables such as the number of coil turns.
The numbers of poles and slots are also discrete variables in motor design. In addition, materials are also essential design variables that determine performance and production cost.
JMAG optimization feature supports both continuous and discrete variables. The material support was also introduced in JMAG-Designer Ver.24.2.
This poster presents case studies of geometry optimization including the number of turns for an induction heating coil, core material optimization for a reactor and pole-slot number optimization for an IPM motor, and discusses the usefulness of discrete optimization.

When performing geometry optimization, setting appropriate ranges for dimensional variables is crucial due to the possibility of geometry collapses.
To conduct wider range optimization, the number of variables increases, making it progressively difficult to determine ranges while ensuring shape integrity.
Range Finder in JMAG can automatically determine a appropriate optimization range by searching for the geometry validity range for the target dimensional variables.
However, good performance design obtained by the optimization can sometimes be difficult to manufacture, such as when components are positioned too close to one another.
To resolve this issue, the Range Finder now supports constraint conditions for critical design dimensions that vary with the optimization parameters.
This poster demonstrates how to obtain manufacturable designs that satisfy both requirements and constraints, using examples like motors, induction heating coils, and solenoids.

Electrical machines have recently become increasingly complex, with more design variables and operating conditions to consider.
As a result, a large amount of computational resources is required, and users are often forced to give up on performing the calculations.
Therefore, JMAG proposes ultra-large-scale distributed execution with massive numbers of calculation jobs. This approach makes optimization calculations and JMAG-RT model creation, previously considered impossible within practical timeframes, feasible.
This poster presents examples such as surrogate model creation for offline optimization and JMAG-RT model generation for multiphase motors.
Such large-scale distributed execution requires not only powerful computing hardware but also appropriate software. To meet this need, JMAG is introducing the Power Simulation License (PSL) lineup with the launch of PSL1000.
Through this poster, we demonstrate how large-scale distributed execution, combined with high-performance computing and PSL1000, enables innovative electrical machine design.

For multi-case calculations, including optimization tasks, increasing the number of concurrent jobs effectively reduces computation time.
While multi-node cluster configurations were typically used for this purpose, modern PCs now feature increased core counts, enabling even a single machine to benefit from improved calculation speeds through concurrent job execution.
JMAG now offers new licenses allowing up to 16 or 32 jobs to run simultaneously, enabling distributed processing of multi-case calculations across multiple connected Windows machines.
Building a small-scale distributed computing environment on your own PCs is now easy and cost-effective. We invite you to take advantage of this opportunity.
This seminar will explain how to connect multiple Windows machines for distributed execution. It will also cover JMAG features?such as file output control and license management?designed to maximize machine performance.

Electrical equipment design has reached a high level of maturity, and surpassing current designs requires ideas free from conventional constraints and exploration of a broader design space.
Performing these tasks manually demands exceptional skill from designers and an enormous amount of time.
To reduce time, cut costs, and eliminate dependency on individual expertise, automated design proves highly effective, with optimization being an especially powerful tool.
Among these, topology optimization offers a high degree of shape freedom and holds the potential to generate innovative design concepts.
However, this very freedom introduces a challenge: reaching a good solution often requires extensive computational time.
To address this, we have added a feature that allows arbitrary specification of initial individuals, such as existing topology optimization results. Compared to random generation, this increases the proportion of individuals satisfying constraints and accelerates the progression of the Pareto front.
As a further enhancement, we are developing functionality to set initial individuals directly from existing CAD data.
In this poster, we take on the challenge of generating initial individuals based on existing shapes and exploring whether we can achieve designs that outperform them.
Additionally, we conduct sensitivity analysis on the results to understand why the obtained shapes perform well.

Accurate evaluation of AC losses and magnetic flux due to coil ends requires high-precision modeling of coil end shapes and winding arrangements.
However, even when using CAD for design, manual adjustments are often required to handle high-density coil layouts and component interferences, which tends to increase the overall design workload.
This poster introduces a method for easily and quickly generating complex winding shapes and setting conditions using JMAG’s coil template function in conjunction with the winding editor.
Application examples for radial and axial gap motors, as well as tips for interference avoidance and CAD collaboration, are also presented.

Calculations with movement of moving parts such as axial gap motors and induction heating must use the extended slide function because the gap is not a simple cylindrical or flat surface.
In JMAG-Designer Ver.24.2 and later, the extended slide function has been improved to enable more accurate calculations in a shorter time.
Additionally, the automatic element size determination function for 3D semi-automatic meshing has been improved.
This poster will show calculation examples for axial gap motors and induction heating, and introduce the effects of improvements.

Efficiency maps are widely used to characterise the operating range of traction machines, typically defined by current and voltage limits. However, the resulting power at these limits can exceed the maximum power available from the battery. Additionally, certain applications impose rules that restrict the maximum deliverable power across different operating quadrants. Ignoring those limits will lead to overestimations of the machine’s usable operating region. Applied to a 250kW traction motor, this study shows how power limitations influence the actual operating region, underlining the necessity of incorporating these constraints in machine design.

Efficiency maps are widely used to describe the operating characteristics of traction machines, and drive-cycle analyses based on these maps have become a standard approach for evaluating machine performance. However, such analyses are often conducted under static conditions, which can overlook important system-level effects. In high-performance contexts such as motorsport, rapid battery energy draw can induce voltage fluctuations, impacting machine efficiency and losses. By integrating these fluctuations into drive cycle simulations, the true performance of a 250kW traction motor can be evaluated. Results illustrate the significance of system-level dynamics on high-power machine operation.

In the development of induction heating coils, the optimum coil design is required depending on the parts to be heated.
In order to efficiently develop such heating coils, simulation is used for design.
To simulate induction heating, it is necessary to consider the temperature dependency of the material, and it is also necessary to have a mesh that can accurately capture the eddy current distribution.
It is also important to consider the cooling process after heating to prevent deformation of the heated object.
This poster will explain the concept of appropriate mesh generation for accurately simulating induction heating phenomena, as well as examples of induction heating calculations that take into account the cooling process, and how to set them up.

×

Miniaturization and high-frequency operation of chopper inductors used in DC-DC converters present conflicting requirements from the perspective of loss increase. Therefore, a trade-off design across a wide frequency range is essential.
Using JMAG, seamless evaluation over a broad frequency spectrum?from low to high frequencies?is possible through electromagnetic field analysis that accounts for displacement currents.
This poster presents modeling approaches for obtaining the frequency characteristics of impedance and loss, using laminated and spiral-type chopper inductors as examples.

In the design of transformers for converters, miniaturization and operation at higher frequencies can lead to a decrease in the coupling coefficient and an increase in losses.
Therefore, it is necessary to perform electromagnetic field analysis that takes displacement currents into account and to evaluate the transformer over a wide frequency range.
This poster presents a modeling approach for obtaining the frequency characteristics of impedance and coupling coefficient, using a transformer for an LLC resonant converter as an example.

In recent years, with the widespread adoption of wide bandgap semiconductors such as SiC and GaN, power converters, including chopper circuits, have increasingly shifted toward higher-frequency operation.
While higher frequencies are essential for achieving compact and high-efficiency systems, they simultaneously complicate impedance characteristics due to the influence of parasitic components such as inductors’ skin effect, proximity effect, and inter-winding stray capacitance.
This leads to increased losses and heightened EMI noise.　Accurately predicting impedance characteristics that account for these high-frequency phenomena during the design and optimization phase of equipment is critically important.
Here, we demonstrate that by employing both phenomenon analysis through magnetic field simulation considering displacement currents and a high-precision equivalent circuit model reflecting the physical structure of chopper inductors and high-frequency-specific phenomena, impedance characteristics with sufficient accuracy for practical applications can be efficiently obtained.

In recent years, driven by the proliferation of electric vehicles and energy-saving requirements for industrial equipment, motor drive inverters have increasingly adopted wide bandgap semiconductors such as SiC, advancing toward even higher switching speeds.
While faster switching contributes to higher efficiency, it also increases common-mode voltage, raising the risk of shaft current generation due to bearing insulation breakdown.
Furthermore, shaft currents cause electrical erosion of bearings, significantly reducing motor reliability.
From the perspectives of ensuring reliability and EMI countermeasures, accurately predicting high-frequency phenomena such as common-mode voltage and shaft current during the design stage is critically important.
Here, we present a case study where high-frequency phenomena in a motor were analyzed by representing high-frequency paths as equivalent circuits, considering parasitic components in each part, and directly coupling with FEA.

As power density increases, thermal design must be performed under stringent temperature constraints, particularly for traction motors.
JMAG’s thermal analysis functions for motors are being developed with ease of use in mind.
For example, heat transfer phenomena between contacting parts or in air gaps, as well as effects of cooling jackets, shaft cooling and spray cooling can be considered through simple settings of conditions and thermal circuit elements.
Furthermore, to help motor designers easily begin thermal analysis, JMAG-Express provides thermal design scenarios utilizing these functions.
This poster introduces useful features for performing thermal analysis on high-power motors.

In motor design, evaluating cooling performance is now essential, and air cooling is commonly used as the cooling method for industrial induction motors.
JMAG’s thermal analysis allows users to handle contact thermal resistance between parts and natural or forced convection cooling outside the housing with simple settings.
Additionally, the introduction of flow circuit enables analysis that considers cooling through ventilation inside the motor.
JMAG-Express includes pre-installed thermal design scenarios utilizing these features.
Using these scenarios allows users to proceed from setup to result evaluation with minimal steps.
This poster introduces useful features for thermal analysis of air-cooled motors.

Analyzing high-efficiency electrical equipment requires accurate modeling of magnets, which produce magnetomotive force.
JMAG has a wide selection of magnetization patterns to choose from, but magnetization analysis is effective when simulating more complex magnetization states or incomplete magnetization.
When the magnet becomes hot or is subjected to a strong demagnetizing field during equipment operation, magnet modeling is used, which can handle irreversible demagnetization.
This concept can also be applied to demagnetization and magnetization during operation.
In this poster, analyses by comparing it with the magnetization process can be understood.
Modeling of irreversible demagnetization due to heat and demagnetizing fields are also explained.

As electrical equipment becomes smaller and more powerful, it is necessary to consider the extrapolation of the BH curve, which is effective in high magnetic flux density regions, the anisotropy of electrical steel sheets, and the effects of processing distortion and stress.
It is also becoming increasingly important to consider characteristics that depend on the operating environment, such as the temperature dependence of the magnetic properties of steel materials during induction hardening, and the frequency dependence of core permeability in high-frequency applications.
This poster will explain magnetic property modeling of soft magnetic materials, which is useful for estimating material-related factors when there is a discrepancy between analysis and measurement.

Electrical devices are becoming increasingly high-frequency.
As a result, the effects of AC copper loss and harmonic iron loss can no longer be ignored.
With regard to the latter in particular, it is important to understand the characteristics of the play model, 1-D method, and anomalous eddy current loss modeling, which will see increased use in the future.
In addition, with the miniaturization of equipment, the effects of the building factor can no longer be ignored.
In this poster, we will show how these modeling techniques affect losses in order to evaluate losses accurately.

Accurate loss analysis is critical for designing high-efficiency electrical machines. The conventional loss calculation method using iron loss tables requires measured iron loss values at the operating frequency and magnetic flux density. However, as electrical machines become higher frequency and more efficient, it increasingly operates in regions where measuring iron loss values is difficult.
As an alternative method that avoids the need for frequency-specific iron loss measurements, JMAG offers an approach combining eddy current calculation with a play model. However, this method does not take account for excess loss, potentially leading to underestimated loss. To further improve loss analysis accuracy, we are investigating modeling approach for excess loss. This poster describes the modeling method for excess loss currently under consideration.

The efficiency map generation function provided by JMAG-RT Viewer will be discontinued at the end of December 2025.
In response, JMAG-Designer 25.0 has expanded its efficiency map generation capabilities using JMAG-RT models, enabling evaluation of a wider range of motor types and connection methods, as well as a greater variety of physical quantities. In addition, compared to JMAG-RT Viewer, JMAG-Designer offers the advantage of shorter generation times.
This poster introduces the efficiency map generation function using JMAG-RT models in JMAG-Designer, covering the range of supported models, usage procedures, and detailed features, as well as methods for utilizing this function to verify the characteristics of created models.

In the design of superconducting devices, simulation-based evaluation of temperature and mechanical stress is crucial to prevent serious risks such as quenching and structural failure.
However, superconducting analysis presents significant challenges due to the nonlinear behavior of materials, which depends on temperature and the anisotropic properties of the magnetic fields, as well as the increased computational demands associated with complex geometries.
JMAG enables coupled analysis of magnetic fields, thermal dynamics, and structural mechanics, allowing the evaluation of temperature and stress in superconducting systems.
Furthermore, JMAG continues to enhance material modeling, improve the convergence of nonlinear computations, and develop advanced modeling functions for superconducting coils and cables.
These advancements contribute to simulation solutions that are well-suited for practical applications.
This poster will introduce JMAG’s superconducting analysis capabilities through case studies involving rotating machines and coils/cables.

Superconducting technologies enable compact, high-field, and low-loss devices across fields like medicine, transportation, and energy.
However, critical challenges such as quenching and structural failure require thorough risk assessment.
Low-temperature superconductors (LTS) demand precise thermal management due to their narrow temperature margins.
In contrast, high-temperature superconductors (HTS) are sensitive to mechanical stress, making structural integrity a key design concern.
This poster presents multiphysics analysis case studies for both LTS and HTS coils to support more reliable superconducting system design.

In recent years, the miniaturization and increased output of electrical machines have progressed, leading to growing demands for higher performance and quality.
Among these, axial flux motors?capable of delivering high output in a thin form factor?are gaining significant attention.
Optimization calculations are widely used to generate design proposals, making it possible to discover designs that were previously unattainable through manual efforts.
However, preparing the necessary input data?such as geometry, design variables, mesh, and evaluation criteria?can be time-consuming.
JMAG-Express addresses this challenge by providing templates for geometry and evaluation settings, significantly reducing the workload.
Moreover, its evaluation capabilities include not only magnetic characteristics but also thermal properties, enabling multifaceted assessments and reducing rework in later stages.
This poster presents a case study on axial flux motor optimization using JMAG-Express.

Demands for lower noise and vibration (NV) in motor-equipped devices, such as EV powertrains, are continuously increasing. Performing evaluation and implementing mitigations of NV concurrently from the initial stages of magnetic design is highly effective for shortening the overall design period and reducing costs. This requires an environment where NV evaluation and mitigation can be quickly examined within the magnetic design software.
JMAG allows users to evaluate system vibration, using the electromagnetic force as the excitation force, simultaneously with the motor’s magnetic field analysis. Furthermore, it is possible to evaluate the time and spatial harmonic components of electromagnetic force and flux density, as well as perform optimization aimed at goals such as resonance avoidance, using equipment dimensions and input/drive conditions as design variables.
This poster introduces JMAG’s NV design solutions that can be utilized in the magnetic design process.

Model-based development is essential for achieving high-precision and efficient system design. In particular, leveraging MIL (Model-in-the-Loop) for control design in parallel with plant design and performing verification using HIL (Hardware-in-the-Loop) with actual ECUs are highly effective approaches.
However, to prevent rework in MBD (Model-Based Development) utilizing MIL/HIL, a highly accurate plant model that faithfully reproduces real machine behavior is required.
JMAG-RT models provide such high-precision plant models for both control design in MIL and verification in HIL. They not only consider magnetic saturation and spatial harmonics but also support fault analysis such as open-circuit conditions, accurately reproducing phenomena that occur in real machines.
This poster introduces the features of JMAG-RT models and the MIL/HIL environments they support. Furthermore, through case studies using JMAG-RT models, we explain the value of high-precision plant models.

In recent years, permanent magnet synchronous motors (PMSM) have been widely adopted in electric vehicles (EVs) and other applications due to their high efficiency.
Consequently, improving noise and vibration (NVH) characteristics has become a critical challenge from a comfort perspective.
The primary source of NVH excitation is the electromagnetic force within the motor.
In particular, minute rotor positional deviations (radial eccentricity and axial offset) caused by manufacturing tolerances generate unexpected electromagnetic excitation forces, becoming a factor that worsens noise and vibration.
To accurately predict the motor’s NVH performance at the design stage, it is extremely important to calculate not only major electromagnetic force components like torque but also these minute electromagnetic excitation forces with high precision.
In finite element analysis (FEA), the accuracy of electromagnetic force calculations is significantly influenced by mesh quality.
While increasing overall mesh detail is effective for improving accuracy, it carries the risk of exponentially increasing computational cost.
Here, we propose specific mesh modeling guidelines to capture the unique physical phenomena associated with rotor displacement (radial eccentricity and axial offset) and achieve a balance between computational cost and accuracy.

By using “Efficiency Map Study” to obtain efficiency maps for rotating machines, you can compare the performance of different design candidates and narrow down options through optimization.
Furthermore, by taking advantage of a wide range of configuration options – such as adjusting operating points to be calculated, considering harmonic losses, and accounting for component temperatures – you can generate maps that meet your required level of accuracy.
In this poster, we present the accuracy and creation speed of efficiency maps using various PMSM (Permanent Magnet Synchronous Machine) and EESM (Externally Excited Synchronous Machine) models.
Finally, we will introduce our ongoing efforts to address commonly requested feature improvements from our customers.

By using “Efficiency Map Study” to obtain efficiency maps for rotating machines, you can compare the performance of different motor types and design candidates and narrow down options through optimization.
Furthermore, by leveraging a wide range of configuration options – such as adjusting operating points to be calculated, applying AC loss considerations, and accounting for component temperatures – you can generate maps that meet your required level of accuracy.
In this poster, we present the accuracy and creation speed of efficiency maps using various induction machine models.
Finally, we will introduce our ongoing efforts to address commonly requested feature improvements from our customers.

Electrical equipment design involves pursuing how far performance requirements can be improved or reduced while meeting constraints such as cost and standards.
In this regard, data-driven design, which makes decisions based on a wide range of data, is advocated and has become possible thanks to improvements in software and hardware performance.
When performing data-driven design in JMAG, global exploration is performed using surrogate models, and optimization problem and filtering conditions are determined while obtaining an overview in JMAG Design Explorer.
For machine type that meet the conditions, the impact of dimensional tolerances and component temperature on performance is understood through parametric analysis, and design policies are established to make the design more robust.
This is a common design process not only for motors, but for a variety of applications, and JMAG is currently developing data-driven design.
This poster will introduce case studies of data-driven design using JMAG, as well as future development plans.

Wireless power transfer systems are being considered as a method of charging electrical devices such as electric vehicles.
The main components are the windings that generate and receive magnetomotive force, and the core that suppresses leakage magnetic flux and improves power transmission efficiency, and there is a need to maximize the coupling coefficient and minimize losses.
Such designs are difficult to achieve through experience, intuition, or a small number of trials, but by using JMAG’s optimization calculation functions, it is possible to automatically and efficiently explore designs.
This poster will explain examples of optimizing the winding shape and layout, as well as the core shape.

In motor design, accurate evaluation of harmonic components in current is crucial, as they affect losses and excitation forces. However, in the early stages of electromagnetic design, ideal waveforms without harmonics are often used due to concerns about computational cost, resulting in insufficient reflection of control influences.
With JMAG, motor behavior analysis including control circuits can be performed simply by inputting design variables, making it feasible to consider control effects from the initial design stage.
This poster compares motor designs that incorporate current waveforms with harmonic components from the beginning, versus those using conventional ideal waveforms, to evaluate the effectiveness of the design methodology. Designing based on actual current waveforms enables lower losses and reduced heat generation, which can lead to cost reductions through simplified material selection and cooling systems. Furthermore, we examine the potential to reduce risks such as excessive losses, thermal runaway, and thermal demagnetization during prototyping.
From these perspectives, we present the concrete advantages of considering harmonic components in motor design from multiple angles.

We have received requests to understand current usage status in order to operate with the appropriate number of licenses when centrally managing licenses or using them at multiple locations.
JMAG provides a function that can understand usage status from the license server log.
In JMAG-Designer Ver. 25.0 and later, you will be able to understand the license shortages, allowing you to make decisions about adding licenses based on specific information.
Furthermore, if license usage becomes concentrated, there may not be enough licenses available for immediate use.
The license server settings include a function to control users and usage limits, to ensure fair license usage among each location and user.
By configuring your license server to suit your company’s usage, you can make effective use of your licenses among multiple users.
This poster introduces the license usage tracking feature to help you make appropriate license investments, and how to make effective use of licenses among multiple users.

To advance the design of electrified systems in a model-based approach without rework and while improving design quality, it is essential to consider not only magnetic characteristics but also thermal and noise/vibration aspects from the early stages of system-level design alongside plant design.
JMAG-RT provides plant models suitable for system-level design in model-based development, supporting features such as thermal equivalent circuit models and automatic circuit generation for thermal management.
This poster introduces the characteristics, limitations, and workflows of JMAG-RT models used in system design, along with practical application examples. Case studies include cooling performance evaluation for thermal management and radial force assessment acting on teeth for NVH analysis, highlighting the importance of addressing thermal and noise/vibration considerations from the initial design phase.

In recent years, the demand for higher power density in motor design has driven an increase in maximum rotational speed. Consequently, the centrifugal forces acting on rotating components have intensified, leading to greater mechanical stress on core materials and a higher risk of structural failure.
Traditionally, magnetic and structural aspects have been evaluated independently, which can hinder design optimization and reduce overall efficiency. By conducting a multi-disciplinary evaluation that simultaneously considers magnetic characteristics and mechanical strength, trade-offs between these domains can be identified early in the design process. This integrated approach helps minimize design rework, shorten development cycles, and enhance overall reliability.
This poster introduces a method for evaluating mechanical stress in motor design, supported by case studies that demonstrate the effectiveness and advantages of multi-disciplinary evaluation of magnetic and structural performance.

Mounting a resolver near the motor helps reduce system size, but it also increases susceptibility to leakage magnetic flux.
This flux can distort the resolver’s output signal and reduce angle detection accuracy.
This poster outlines a method for analyzing magnetic flux paths and presents case studies of effective countermeasures.