Journal of Southwest Petroleum University(Science & Technology Edition) ›› 2023, Vol. 45 ›› Issue (3): 154-162.DOI: 10.11885/j.issn.1674-5086.2020.11.06.01

• PETROLEUM MACHINERY AND OILFIELD CHEMISTRY • Previous Articles     Next Articles

Design and Optimization Analysis of Downhole Linear Generator Based on Orthogonal Test

ZHONG Gongxiang1, SHEN Wei1, LEI Pengyan2, SONG Hua1, ZHONG Shengji1   

  1. 1. MOE Key Laboratory of Oil and Gas Equipment, Southwest Petroleum University, Chengdu, Sichuan 610500, China;
    2. Department of Transportation and Municipal Engineering, Sichuan College of Architectural Technology, Chengdu, Sichuan 610399, China
  • Received:2020-11-06 Online:2023-06-10 Published:2023-07-07

Abstract: Aiming at the disadvantage of low power generation in the existing downhole power supply mode and combining the advantages of linear power generation, a new cylindrical downhole linear induction power generation scheme is proposed, which generates induced current by the relative motion between the sucker rod and the oil pipe. According to the principle of existing electrical machinery, we complete the structural design of the cylinder type permanent magnet linear generator; then we use Ansoft Maxwell to analyze the no-load flux density, no-load induced electromotive force, resistive load and the power generation performance of the cylindrical permanent magnet generator under the condition of actual sealing, and verify the validity of the generator design. Finally, the key structural parameters are optimized by using the orthogonal experimental optimization method, taking distortion rate and power generation as the optimization objectives. The results show that the generator has low harmonic distortion rate, high power and good stability no matter under load or no load. It can effectively solve the problems of low efficiency and unstable performance of existing downhole generators.

Key words: underground generator, automatic power supply, power generation performance analysis, orthogonal test, optimization design

CLC Number: