# Designing High-Power-Density Electric Motors for Electric Vehicles with Advanced Magnetic Materials

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## Abstract

**:**

## 1. Introduction

#### 1.1. State-of-the-Art

#### 1.2. Motivation

#### 1.3. Paper Organization

## 2. Application of Advanced Electromagnetic Materials in EV Motors

#### 2.1. Soft Magnetic Materials

#### 2.1.1. Thin Electrical Steel Sheets

#### 2.1.2. High Silicon Electrical Steel Sheets

#### 2.1.3. Amorphous Ferromagnetic Metal

#### 2.1.4. Soft Magnetic Composite

#### 2.2. Magnetic Properties of SMC

#### 2.3. Conducting Materials

## 3. Advanced Modeling and Analysis

#### 3.1. Measurement of Magnetic Properties under 2D/3D Vectorial Magnetization

#### 3.2. Modeling of 2D/3D Vectorial Magnetic Properties

**B**(magnetic flux density) and

**H**(magnetic field strength) vectors, and associated core loss, some mathematical models of the 2D/3D vectorial magnetic properties have been established, which are essential for magnetic field analysis of electric motors.

**B**and

**H**vectors, and their relationship should be described in a matrix form as below [123,124,125,126,127,128]:

_{ij}is the reluctivity matrix (i,j = x,y,z in rectangular coordinate or i,j = r,θ,z in cylindrical coordinate). According to the Maxwell’s equations, in magnetic static field analysis, the relation between magnetic vector potential

**A**and the applied current density vector

**J**

_{0}can be derived as

**J**

_{0}can be written as (3). The equations for J

_{y}and J

_{z}can be derived in a similar way.

#### 3.3. Applications of 2D/3D Rotational Core Loss Models

_{t}represents the core loss caused by an ellipsoidal rotating

**B**, P

_{r}is the corresponding loss due to a circularly rotating

**B**with the same peak value and frequency, and P

_{a}is due to an alternating

**B**. Additionally, R

_{B}denotes the axis ratio of the ellipsoidal

**B**.

_{hr}is computed using Equations (5) and (6), where f, B

_{P}, and B

_{s}are, respectively, the frequency, peak value, and saturated value of flux density, and a

_{1}, a

_{2}, and a

_{3}are coefficients. These models were employed to estimate the core loss of a PM motor and achieved better accuracy. In 2005, Guo et al. [132] applied this improved model to calculate the core loss of a PM claw pole motor with an SMC stator core, resulting in a high level of accuracy when compared with experimental data obtained from a motor prototype.

_{P}the magnitude of the circular B vector, B

_{s}the saturation flux density. A

_{1}, a

_{2}, and a

_{3}are all coefficients that can be obtained by curve-fitting the data.

## 4. Advanced Design and Optimization

## 5. Discussions and Conclusions

#### 5.1. Remaining Challenges

- (1)
- The lack of sufficient fundamental property data for electromagnetic materials, such as the relationship between magnetic field strength and flux density under various conditions such as magnetization patterns, magnitudes, frequency, temperature, mechanical stress, DC bias, and magnetostriction;
- (2)
- The need for system-level design optimization of the entire PMSM drive system for optimal performance since assembling individually optimal components such as motor and inverter cannot guarantee optimal system performance. The interaction of multiphysics effects, such as thermal and stress characteristics, should also be considered to improve the accuracy of iron loss prediction for PMSMs, reducing computational cost and providing better accuracy;
- (3)
- The importance of using new materials or high-quality manufacturing in EV drive systems design optimization. New materials such as SMC have great potential for designing electrical machines with high performance and/or low-cost and novel topologies. Future robust design optimization should fully consider manufacturing tolerances, material diversities, and assembling errors to present a comprehensive solution for high quality manufacturing and design;
- (4)
- The need for effective control circuit design for dynamic and steady-state performances of PMSM drive systems. Traditional control algorithms including field-oriented control (FOC), direct torque control (DTC), and model predictive control (MPC) have been developed and employed successfully, but are challenging to guarantee satisfactory performance in the presence of parameter uncertainties and external disturbances during changing operating conditions. Future development should focus on coordinated control strategies at both system and subregion levels;
- (5)
- The challenge of achieving effective modeling with sufficient accuracy and reasonable computation speed using existing mathematical models of material properties. There is a trend towards designing electric motors and drives with digital twin (DT)-based models, optimizing motor performance, as well as manufacturing and operation processes throughout the entire cycle of motor life.

#### 5.2. Comparison between Vectorial Magnetic Properties and Conventional Alternating Properties

#### 5.3. Benefits

## Author Contributions

## Funding

## Data Availability Statement

## Conflicts of Interest

## Abbreviations

AM | Amorphous metal |

DT | Digital twin |

DTC | Direct torque control |

2D | Two-dimensional |

3D | Three-dimensional |

EV | Electric vehicle |

FOC | Field-oriented control |

HTS | High-temperature superconductor |

MMM | Multi-level, multi-objective, multi-disciplinary |

MPC | Model predictive control |

PM | Permanent magnet |

PMSM | Permanent magnet synchronous motor |

PV | Photovoltaic |

SRM | Switched reluctance motor |

Syn-RM | Synchronous reluctance motor |

SST | Square specimen tester |

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**Figure 2.**Experimental results of SMC samples at 50 Hz: (

**a**) B-H relation and associated core loss under 1D alternating sinusoidal B; (

**b**) B-H relation under 2D circularly rotating B; and (

**c**) B-H relation under 3D spherical B.

**Figure 3.**A 3D vectorial magnetic property measurement system: (

**a**) block diagram, and (

**b**) structure of 3D view.

**Figure 7.**Measured core losses of an SMC sample under (

**a**) alternating and (

**b**) circularly rotating magnetizations with different peak values and frequencies of flux density.

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**MDPI and ACS Style**

Guo, Y.; Liu, L.; Ba, X.; Lu, H.; Lei, G.; Yin, W.; Zhu, J.
Designing High-Power-Density Electric Motors for Electric Vehicles with Advanced Magnetic Materials. *World Electr. Veh. J.* **2023**, *14*, 114.
https://doi.org/10.3390/wevj14040114

**AMA Style**

Guo Y, Liu L, Ba X, Lu H, Lei G, Yin W, Zhu J.
Designing High-Power-Density Electric Motors for Electric Vehicles with Advanced Magnetic Materials. *World Electric Vehicle Journal*. 2023; 14(4):114.
https://doi.org/10.3390/wevj14040114

**Chicago/Turabian Style**

Guo, Youguang, Lin Liu, Xin Ba, Haiyan Lu, Gang Lei, Wenliang Yin, and Jianguo Zhu.
2023. "Designing High-Power-Density Electric Motors for Electric Vehicles with Advanced Magnetic Materials" *World Electric Vehicle Journal* 14, no. 4: 114.
https://doi.org/10.3390/wevj14040114