IM to IPM design transformation using neural network and DoE approach considering the efficiency and range extension of an electric vehicle

Demir, Uğur

doi:10.1007/s00202-021-01378-3

Cited by 6 publications

(7 citation statements)

References 27 publications

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“…In the literature, different rotor structures of IPM motors are proposed. These structures can be classified as V -shaped, double magnet shape, delta shape, hybrid delta shape, hybrid double V- shape, rectangular single pole and multi-barrier magnet [ 35 , 36 ].…”

Section: Specification Of the Designed Multi-barrier Interior Permane...mentioning

confidence: 99%

Design and optimization of a high-performance multi-barrier IPMS motor for an electric scooter and bicycle

Gör,

Dalcalı

2024

R. Soc. Open Sci.

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Acknowledging the growing importance of electric vehicles (EVs) in the face of environmental concerns and increasing mobility needs, this study focuses on enhancing the performance of the electric motor, a critical component in EVs. The electric motor of these battery-powered vehicles is expected to have optimal characteristics and efficiency. This paper presents a comprehensive investigation into the design and optimization of a multi-barrier interior permanent magnet synchronous motor tailored for e-scooters and electric bicycles. A multi-barrier rotor structure is proposed and analysed through finite element method simulations to optimize key design parameters. The parametric analysis examines the influence of geometric variables on key motor performance criteria, including efficiency, cogging torque and weight. A correlation analysis of the variables was conducted. A very high positive correlation (0.999) was revealed, especially between the ‘magnet duct dimension parameter’ and efficiency. A very high negative correlation (−1) was found between ‘distance from duct bottom to shaft surface’ and efficiency. The optimized motor design achieves a theoretical improvement of around 7% in efficiency, reaching an overall efficiency of 89.86%. This study highlights the consideration of multiple factors such as efficiency, cogging torque and weight in the design process for the development of sustainable and high-performance EV motor designs.

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Section: Specification Of the Designed Multi-barrier Interior Permane...mentioning

confidence: 99%

Design and optimization of a high-performance multi-barrier IPMS motor for an electric scooter and bicycle

Gör,

Dalcalı

2024

R. Soc. Open Sci.

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“…The power transferred by the vehicle traction motor can be defined with Equations ( 20)-( 22) [18]. Since this study has a rear-wheel drive system, the power distribution must be rearranged.…”

Section: 𝑟̇= 𝑀 𝑧 𝐼 𝑧mentioning

confidence: 99%

“…If not, this motor variation is added to the previous data set and the ANN is re-trained. Then, the ANN is run again to obtain a new motor variation, and the cycle continues to check whether it meets the minimum performance requirements by analyzing it again [13,18]. The following steps that summarize the process are shown in Figure 13a,b.…”

Section: Optimization Algorithmmentioning

confidence: 99%

Intelligent Design Optimization for Traction and Steering Motors of an Autonomous Electric Shuttle under Driving Scenarios

Demir,

Ehsani,

Demir

et al. 2024

Electronics

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Electrified autonomous vehicles have become quite popular and have a wide range of applications. The traction and steering motors to be used on an electrified autonomous vehicle are designed considering the lateral and longitudinal forces in the environment where the vehicle operates, and they are selected with extra safety margins and “over-engineering” features. This causes wastage of rare earth elements, along with both cost and energy inefficiencies. For autonomous shuttle vehicles, traction and steering performances can be analyzed based on driving scenarios. The reference speed and steering signals for the selected driving scenarios were run on a dynamic vehicle model and the minimum performance requirements for the traction and steering motors were determined. Then, the determined design parameters by DoE (Design of Experiments) were trained in two different ANN (Artificial Neural Networks) models created for motor models. The trained ANN models were run according to the minimum performance criteria and predicted motor models with new design parameters for the traction and steering motors. The performance results of the predicted traction and steering motor models showed a significant improvement in terms of the minimum performance requirements.

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“…It is widely used in the literature to reduce simulation times and costs in optimization processes. In addition, it is seen that it is used to create valuable data sets for data-based optimization and to increase efficiency [24][25][26][27][28][29][30]. In this study, DoE is used to generate datasets and calculate objective functions.…”

Section: Figure 3 Teardown Studies and Detailed Component Explanation...mentioning

confidence: 99%

Comparative Design Improvement of the Growing Rod for the Scoliosis Treatment Considering the Mechanical Complications

et al. 2023

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In this study, the focus is on an implant used in the treatment of early-onset scoliosis called magnetically controlled growing rods (MCGR). The primary goal of the study is to address and propose solutions for the mechanical problems reported in the literature concerning MCGR. The problems of the MCGR are mainly due to excessive stress and mechanical bearing problems. Therefore, an MCGR removed from a patient is teardown and geometrically modeled. Then, eleven design parameters are determined on the MCGR for the mechanical problems experienced and these are evaluated by mechanical analysis over 14 control points. In this study, analysis processes are carried out with L12 orthogonal array for eleven design parameters and 2 levels using Taguchi's experimental design method (DoE). With the obtained data by analyzing the experiments in L12, the fitness functions depending on the design parameters are created for 14 control points. Since the problem is multi-objective, a non-dominated sorting genetic algorithm (NSGA II) and multi-objective particle swarm optimization (MOPSO) are used to minimize stress and displacement in existing mechanical problems using fitness functions. The obtained design models from NSGA II and MOPSO are analyzed and evaluated in comparison with the existing mechanical model obtained through preoptimization teardown study of MCGR.

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IM to IPM design transformation using neural network and DoE approach considering the efficiency and range extension of an electric vehicle

Cited by 6 publications

References 27 publications

Design and optimization of a high-performance multi-barrier IPMS motor for an electric scooter and bicycle

Design and optimization of a high-performance multi-barrier IPMS motor for an electric scooter and bicycle

Intelligent Design Optimization for Traction and Steering Motors of an Autonomous Electric Shuttle under Driving Scenarios

Comparative Design Improvement of the Growing Rod for the Scoliosis Treatment Considering the Mechanical Complications

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