|
|
|
| Motion Characteristics of Linear Propulsion Electromagnetic Energy Equipment Based on Dynamic Friction Coefficient Inversion |
| Zhao Wenyue1,2, Yan Rongge1,2, Yang Qingxin3, Wang Xueqian1,2, Zhao Haokai1,2 |
1. State Key Laboratory of Reliability and Intelligence of Electrical Equipment Hebei University of Technology Tianjin 300401 China;
2. Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability of Hebei Province Hebei University of Technology Tianjin 300401 China;
3. Tianjin Key Laboratory of New Energy Power Conversion Transmission and intelligent Control Tianjin University of Technology Tianjin 300387 China |
|
|
|
Abstract In the working process of linear propulsion electromagnetic energy equipment, friction between the armature and rail due to high-speed sliding is one of the important factors affecting its motion characteristics. However, realizing real-time and in-situ friction coefficient measurement is challenging under extreme electromagnetic, thermal, and mechanical shock conditions. Therefore, the friction coefficient between the armature and rails is fixed as the empirical value in the current research. The actual motion characteristics of the armature fail to be accurately captured because the potential impact of its dynamic changes on the performance of the system is ignored. This paper proposes a method based on the dynamic friction coefficient inversion of motion characteristics.
Firstly, a nonlinear mapping relationship between the armature velocity with the armature-rail friction coefficient and the rail inductance gradient during the armature motion is deduced from the observable data measured by the electromagnetic propulsion experiment and the armature kinetics forward model. Then, the inversion model for the armature-rail friction coefficient and rail inductance gradient is established using the improved dynamic particle swarm optimization (DPSO). The computational velocity is corrected in real-time by the measured velocity of the armature to obtain the spatiotemporal characteristics. The friction coefficient between the armature and rails starts to decrease rapidly with increasing armature velocity, then the decreasing trend slows down and finally tends to a stable value.
Then, the model for transient electromagnetic, thermal, and mechanical coupling is established. Motion characteristics of the equipment are analyzed when the friction coefficient is dynamic (DFC) and constant (FFC). Herein, the friction coefficient between the armature and rails is segmented according to velocity, and the parameters of each velocity segment are determined using the nonlinear least squares fitting method. The results show that the dynamic change of the friction coefficient increases the armature current density, magnetic density, and temperature at the same velocity, which greatly affects the temperature of the armature-rail contact surface. A high current density and magnetic induction are necessary to produce enough Lorentz force to overcome the increased friction caused by the dynamic changes in the friction coefficient. Therefore, the simultaneous increase of friction heat and resistance heat causes the temperature difference on the contact surface of the armature rail to increase gradually under DFC and FFC conditions. The temperature difference reaches 522℃ at 0.75 ms.
Finally, an experimental platform for the linear propulsion electromagnetic energy equipment is built to measure the armature velocity and the magnetic induction strength at the rail. Considering the dynamic friction coefficient, the armature velocity and the magnetic induction intensity are close to the measured values, and the calculation accuracy of the model is high, verifying the correctness of the theoretical analysis.
|
|
Received: 19 February 2024
|
|
|
|
|
|
[1] 马伟明. 关于电工学科前沿技术发展的若干思考[J]. 电工技术学报, 2021, 36(22): 4627-4636.
Ma Weiming.Thoughts on the development of frontier technology in electrical engineering[J]. Transactions of China Electrotechnical Society, 2021, 36(22): 4627-4636.
[2] 李兵, 李卫超, 荆从凯. 电磁发射系统研究现状及应用展望[J]. 兵器装备工程学报, 2023, 44(10): 173-181.
Li Bing, Li Weichao, Jing Congkai.Research status and application prospects of electromagnetic launch system[J]. Journal of Ordnance Equipment Engin- eering, 2023, 44(10): 173-181.
[3] 杜佩佩, 鲁军勇, 冯军红, 等. 电磁轨道发射器电磁结构耦合动态发射过程数值模拟[J]. 电工技术学报, 2020, 35(18): 3802-3810.
Du Peipei, Lu Junyong, Feng Junhong, et al.Numerical simulation of dynamic launching process of electromagnetic rail launcher with electromagnetic and structural coupling[J]. Transactions of China Electrotechnical Society, 2020, 35(18): 3802-3810.
[4] 马伟明, 鲁军勇. 电磁发射技术的研究现状与挑战[J]. 电工技术学报, 2023, 38(15): 3943-3959.
Ma Weiming, Lu Junyong.Research progress and challenges of electromagnetic launch technology[J]. Transactions of China Electrotechnical Society, 2023, 38(15): 3943-3959.
[5] 高博, 邱群先, 郄文静, 等. 电磁轨道炮电枢多场耦合分析与试验研究[J]. 电工技术学报, 2020, 35(增刊2): 341-345.
Gao Bo, Qiu Qunxian, Qie Wenjing, et al.Multi-field coupling analysis and experimental research on armature of electromagnetic railgun[J]. Transactions of China Electrotechnical Society, 2020, 35(S2): 341-345.
[6] Liu Shaowei, Du Xiangyu, Guan Jiao, et al.Research on transient contact characteristics of the hyperbolic rail augmented quadrupole launcher[J]. IEEE Transa- ctions on Plasma Science, 2022, 50(10): 3794-3801.
[7] Lin Y, Li J Z, Pan J, et al.Current-carrying wear behavior and the interface evolution of the Cu/Al tribological pair[J]. Engineering Failure Analysis, 2023, 153: 107549.
[8] Brown L, Xu D, Ravi-Chandar K, et al.Coefficient of friction measurement in the presence of high current density[J]. IEEE Transactions on Magnetics, 2007, 43(1): 334-337.
[9] Dai Keren, Yang Yuxin, Yin Qiang, et al.Theoretical model and analysis on the locally concentrated current and heat during electromagnetic propulsion[J]. IEEE Access, 2019, 7: 164856-164866.
[10] 范薇, 苏子舟, 张涛, 等. 增强型电磁轨道炮瞬态温升时空分布[J]. 高电压技术, 2021, 47(9): 3346-3354.
11 Fan Wei, Su Zizhou, Zhang Tao, et al.Spatial- temporal distribution of transient temperature rise in augmented electromagnetic railgun[J]. High Voltage Engineering, 2021, 47(9): 3346-3354.
[11] Zhou Pengfei, Li Baoming.Exergy analysis of the electromagnetic railgun[J]. IEEE Transactions on Plasma Science, 2021, 49(12): 3980-3987.
[12] Li Shizhong, Li Jun, Xia Shengguo, et al.Phase division and critical point definition of electro- magnetic railgun sliding contact state[J]. IEEE Transa- ctions on Plasma Science, 2019, 47(5): 2399-2403.
[13] Cao Bin, Ge Xia, Guo Wei, et al.Analysis of rail dynamic deformation during electromagnetic launch[J]. IEEE Transactions on Plasma Science, 2017, 45(7): 1269-1273.
[14] 李婕, 杨淑英, 谢震, 等. 基于有效信息迭代快速粒子群优化算法的永磁同步电机参数在线辨识[J]. 电工技术学报, 2022, 37(18): 4604-4613.
Li Jie, Yang Shuying, Xie Zhen, et al.Online parameter identification of permanent magnet synchronous motor based on fast particle swarm optimization algorithm with effective information iterated[J]. Transactions of China Electrotechnical Society, 2022, 37(18): 4604-4613.
[15] 周嗣理, 李国丽, 王群京, 等. 基于改进粒子群优化算法的永磁球形电机驱动策略研究[J]. 电工技术学报, 2023, 38(1): 166-176, 189.
Zhou Sili, Li Guoli, Wang Qunjing, et al.Improved particle swarm optimization algorithm based driving strategy research for permanent magnet spherical motor[J]. Transactions of China Electrotechnical Society, 2023, 38(1): 166-176, 189. |
|
|
|
2025, Vol. 40 
