“…Among the various electrical faults, the high-resistance connections (HRC) have received extensive attention due to their potential to cause significant damage to running vehicles directly. The HRC in EVs can be caused by multiple factors such as vehicle vibration, poor workmanship of components, thermal cycling problems [4], and damage of the contact surfaces in high-power circuits due to pitting, corrosion, or contamination [5]. HRC fault can occur in either the single-phase or dual-phase positions of three-phase PMSMs.…”
Section: Owing To the Manufacturing And Installation Errors Ofmentioning
confidence: 99%
“…• Signal injection: inject predefined DC vectors in the 𝑑axis and measure phase currents to detect and isolate HRC problems [4][5][6].…”
Section: Owing To the Manufacturing And Installation Errors Ofmentioning
High-resistance connections (HRC) in permanent magnet synchronous motor (PMSM) drive system is a precursor of uncontrollable overheating or fire. However, the current HRC test environment is typically founded on fixed resistors and lacks the capability to simulate the dynamic characteristics of real-world HRC faults in a manner of stepless regulation. To fill the gap, a flexible HRC injection strategy is proposed in this paper. This signal is stimulated by a high-frequency equivalent circuit regulated by closed-loop hardware feedback mechanism, which is then integrated into a self-developed HRC dynamic test system. Meanwhile, to reduce dependence on online resources, a rapid online diagnosis method for detecting HRC in PMSM is proposed. Based on the two-phase current, the negative-sequence currents are calculated and subjected to Fast Fourier Transform analysis, fulfilling the requirements of low computational burden and real-time performance. Furthermore, the fault indicators derived from the mathematical model of PMSM in abc framework are established to detect the HRC fault, obviating the need for additional voltage sensors. Finally, various experiments are conducted under different loads and rotational speeds. The experimental results show that the proposed simulation system can solve the problems of HRC simulation with quick responses, continuous control, and high robustness in high-power circuits. The results also prove that the proposed diagnosis method can not only effectively detect the location of HRC, but also can precisely calculate the resistance.
“…Among the various electrical faults, the high-resistance connections (HRC) have received extensive attention due to their potential to cause significant damage to running vehicles directly. The HRC in EVs can be caused by multiple factors such as vehicle vibration, poor workmanship of components, thermal cycling problems [4], and damage of the contact surfaces in high-power circuits due to pitting, corrosion, or contamination [5]. HRC fault can occur in either the single-phase or dual-phase positions of three-phase PMSMs.…”
Section: Owing To the Manufacturing And Installation Errors Ofmentioning
confidence: 99%
“…• Signal injection: inject predefined DC vectors in the 𝑑axis and measure phase currents to detect and isolate HRC problems [4][5][6].…”
Section: Owing To the Manufacturing And Installation Errors Ofmentioning
High-resistance connections (HRC) in permanent magnet synchronous motor (PMSM) drive system is a precursor of uncontrollable overheating or fire. However, the current HRC test environment is typically founded on fixed resistors and lacks the capability to simulate the dynamic characteristics of real-world HRC faults in a manner of stepless regulation. To fill the gap, a flexible HRC injection strategy is proposed in this paper. This signal is stimulated by a high-frequency equivalent circuit regulated by closed-loop hardware feedback mechanism, which is then integrated into a self-developed HRC dynamic test system. Meanwhile, to reduce dependence on online resources, a rapid online diagnosis method for detecting HRC in PMSM is proposed. Based on the two-phase current, the negative-sequence currents are calculated and subjected to Fast Fourier Transform analysis, fulfilling the requirements of low computational burden and real-time performance. Furthermore, the fault indicators derived from the mathematical model of PMSM in abc framework are established to detect the HRC fault, obviating the need for additional voltage sensors. Finally, various experiments are conducted under different loads and rotational speeds. The experimental results show that the proposed simulation system can solve the problems of HRC simulation with quick responses, continuous control, and high robustness in high-power circuits. The results also prove that the proposed diagnosis method can not only effectively detect the location of HRC, but also can precisely calculate the resistance.
“…The rotors of the hub motor in electric wheel systems are divided into inner and outer rotor types. 23 With the appearance of planetary gear reducer, the inner rotor is more competitive in terms of power density than the low-speed outer rotor. 24 The experimental object of this paper is an electric wheel comprising a hub motor with an inner rotor, which provides a compact structure and high efficiency.…”
Section: Dynamic Modeling Of Electric Wheelmentioning
The independently controlled electric wheels of distributed drive vehicles provide faster and more accurate actuators for vehicle slip ratio control. Meanwhile, the estimation of the slip ratio of electric wheels has been of vital importance for the dynamics control of distributed drive electric vehicles. However, the conventional slip ratio estimation method is hard to accurately estimate the slip ratio under steering conditions without multiple observations, increasing the cost and introducing errors. Considering that the output torque and motor rotation rate of electric wheels can be accurately collected, the novel slip ratio estimation method takes advantage of the signals of the electric wheels and requires fewer vehicle sensors. Based on the torsional vibration model of electric wheel, the slip ratio estimation method was proposed and validated by simulations and experiments. With the drum dynamometer, the slip ratio estimation method was applied to a single electric wheel for testing, proving the feasibility and accuracy of the proposed method. The slip ratio estimation was finally applied to a fuel cell heavy truck for road tests, of which the results show that the error index is reduced from 0.0152 to 0.0064 compared to the conventional slip ratio estimation method, confirming the good estimation performance achievable via the proposed method.
“…The proposed topology can be employed either as an inverter or a conventional AC power source to generate the harmonic component of the air-gap flux for rotor excitation and the fundamental component to produce the torque. In 13 , the authors presented a comprehensive review on low-cost high-performance ferrite magnets which are more sustainable and have a more stable supply chain for EV applications. Figure 1 Traction electric drive system and additional components for EESMs.…”
Advanced slot and winding designs are imperative to create future high performance electrical machines (EM). As a result, the development of methods to design and improve slot filling factor (SFF) has attracted considerable research. Recent developments in manufacturing processes, such as additive manufacturing and alternative materials, has also highlighted a need for novel high-fidelity design techniques to develop high performance complex geometries and topologies. This study therefore introduces a novel physics-informed machine learning (PIML) design optimization process for improving SFF in traction electrical machines used in electric vehicles. A maximum entropy sampling algorithm (MESA) is used to seed a physics-informed Bayesian optimization (PIBO) algorithm, where the target function and its approximations are produced by Gaussian processes (GP)s. The proposed PIBO-MESA is coupled with a 2D finite element model (FEM) to perform a GP-based surrogate and provide the first demonstration of the optimal combination of complex design variables for an electrical machine. Significant computational gains were achieved using the new PIBO-MESA approach, which is 45% faster than existing stochastic methods, such as the non-dominated sorting genetic algorithm II (NSGA-II). The FEM results confirm that the new design optimization process and keystone shaped wires lead to a higher SFF (i.e. by 20%) and electromagnetic improvements (e.g. maximum torque by 12%) with similar resistivity. The newly developed PIBO-MESA design optimization process therefore presents significant benefits in the design of high-performance electric machines, with reduced development time and costs.
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