The influence of combined strain and constructive solutions for stator insulation of rotating electrical machines on duration of their reliable exploitation

Jokanović, Bojan; Bebić, Milan; Kartalović, Nenad

doi:10.1016/j.ijepes.2019.02.041

Cited by 14 publications

(8 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The drive motor is an energy conversion device [23]. It has two main functions: converting electrical energy into mechanical energy when the vehicle is driving, and then BEVs brake or experience wheel slip, the feedback energy will be stored in the battery system through the powertrain system.…”

Section: Batterymentioning

confidence: 99%

See 1 more Smart Citation

Reliability Study of BEV Powertrain System and Its Components—A Case Study

et al. 2021

View full text Add to dashboard Cite

The powertrain system is critical to the reliability of a battery electric vehicle (BEV). However, the BEV powertrain is a complex system; it includes the motor, motor controller, power distribution unit, battery system, etc. The failure of any of these components may result in the failure of the entire powertrain system and eventually cause serious traffic accidents on the road. However, how much does each component affect the reliability of the entire system, and which components are the most vulnerable in the entire system? These questions are still unanswered today. To develop a reliability design for a BEV powertrain system, it is essential to conduct detailed research by investigating the most vulnerable component parts of the entire powertrain. In the present study, a fault-tree model of the entire powertrain and its subsystems was developed. Based on this model, the failure rates of all components were calculated first. Then, trends in the reliability indices for the entire powertrain and its components were estimated against BEV service life. From the estimation results, we learned that with increased service time, the reliability of the entire powertrain system is indeed much lower than that of its individual subsystems. Moreover, through comparative research, we found that the battery module is the most unreliable component not only of the battery system, but the entire powertrain system. Additionally, it was interesting to find that the reliability of the motor components was higher than that of other subsystem components, but that the reliability indices for the entire motor were not the highest among all the powertrain subsystems studied in this paper. We believe the findings of the present study will be of great significance to an improved understanding of the reliability design and maintenance of BEVs.

show abstract

Section: Batterymentioning

confidence: 99%

“…The drive motor is an energy conversion device [23]. It has two main functions: converting electrical energy into mechanical energy when the vehicle is driving, and then The battery system is mainly used to store electrical energy and is composed of multiple battery cells connected in series and in parallel.…”

Section: Batterymentioning

confidence: 99%

Reliability Study of BEV Powertrain System and Its Components—A Case Study

et al. 2021

View full text Add to dashboard Cite

show abstract

“…Stator insulation can deteriorate via many mechanisms. Reference [16] identifies sources of stator insulation deterioration as mechanical, electrical and thermal stresses. Additional sources are environmental moisture, dirt, chemicals and possible overvoltage for inverter-fed machines.…”

Section: Introductionmentioning

confidence: 99%

Modeling of Insulation Paper Damage in the Assembly of a Solid Slot Winding

Stefe¹,

Jenko

2020

IEEE Access

View full text Add to dashboard Cite

Tight assembly of stator windings with no insulation paper damage is a manufacturing challenge. We evaluate different sets of parts according to the following parameters: magnet wire thickness, stator slot smoothness, length of the straight magnet wire after the slot end, and type and amount of insulation cap at the end of the slot. These parameters have discrete values with small differences between them. The damage criterion is the decrease of the insulation paper breakdown voltage after assembly/disassembly of parts, assembled in a small set of designed experiments. Parameter values, i.e., levels at individual experiments are set by an orthogonal experiment matrix. Repetition of each experiment provides statistical significance. Data analysis shows that the additive model alone is not sufficient due to the high correlation of the parameters' influences. We extend the model to include interparameter influences, which we model by adding a virtual parameter. The extended additive model generates parameter values that do not degrade the insulation paper breakdown voltage within the manufacturing process. These values are verified by repetitions of the control experiment. INDEX TERMS Analysis of variance, breakdown voltage, design for experiments, design for manufacture, dielectrics and electrical insulation, extended additive model, insulation paper damage, insulation testing, interparameter influence, in-wheel motor reliability, matrices, metal-insulator structures, orthogonal matrix experiments, permanent magnet motors, stators.

show abstract

“…Rotating electrical machines are responsible for converting a great amount of worldwide energy into mechanical energy [1]. Mobility, transportation, logistics, construction, production, agriculture, food, automation, and basically any economic activity and industry directly or indirectly depend on rotating electrical machines, as discussed in literatures, e.g., [2][3][4][5][6]. The rapidly evolving industries have suggested that we will be witnessing a further increase in this rate [7].…”

Section: Introductionmentioning

confidence: 99%

Fault Diagnosis of Rotating Electrical Machines Using Multi-Label Classification

et al. 2019

View full text Add to dashboard Cite

Fault Detection and Diagnosis of electrical machine and drive systems are of utmost importance in modern industrial automation. The widespread use of Machine Learning techniques has made it possible to replace traditional motor fault detection techniques with more efficient solutions that are capable of early fault recognition by using large amounts of sensory data. However, the detection of concurrent failures is still a challenge in the presence of disturbing noises or when the multiple faults cause overlapping features. Multi-label classification has recently gained popularity in various application domains as an efficient method for fault detection and monitoring of systems with promising results. The contribution of this work is to propose a novel methodology for multi-label classification for simultaneously diagnosing multiple faults and evaluating the fault severity under noisy conditions. In this research, the Electrical Signature Analysis as well as traditional vibration data have been considered for modeling. Furthermore, the performance of various multi-label classification models is compared. Current and vibration signals are acquired under normal and fault conditions. The applicability of the proposed method is experimentally validated under diverse fault conditions such as unbalance and misalignment.

show abstract

The influence of combined strain and constructive solutions for stator insulation of rotating electrical machines on duration of their reliable exploitation

Cited by 14 publications

References 20 publications

Reliability Study of BEV Powertrain System and Its Components—A Case Study

Reliability Study of BEV Powertrain System and Its Components—A Case Study

Modeling of Insulation Paper Damage in the Assembly of a Solid Slot Winding

Fault Diagnosis of Rotating Electrical Machines Using Multi-Label Classification

Contact Info

Product

Resources

About