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Abstract A comprehensive numerical model was developed to address the performance of a permanent magnet direct current (PMDC) motor which is employed as a small-scale three-bladed horizontal axis ocean current turbine. This numerical model development is presented along with a comparison to experimental data to quantify the motor performance. The proposed experimental design is discussed in detail. Due to the nature of the ocean current turbine, it is required to run it first by applying input power, subsequently to be governed by hydrokinetic energy. Thus, a detailed performance of the PMDC motor is essential when it runs as a motor and generator. Based on our preliminary work, the angular speed of the small-scale turbine is less than 500 rpm. Thus, a combination of the PMDC motor and a planetary gearhead is used to fulfill this low-speed requirement. The gearhead is driven in reverse when operating as a generator which leads to poor efficiency. This efficiency is experimentally derived to be 47.8% at maximum speed of 479.4 rpm at 12V.
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Applying Artificial Intelligence to Optimize Small-Scale Ocean Current Turbine Performance
Abstract A comprehensive artificial intelligence-based motor drive was developed to control the performance of a permanent magnet direct current (PMDC) motor employed as a small-scale three-bladed horizontal axis ocean current turbine. Although the conventional controller performs reasonably in a lab environment where non-linear load is absented; however, for towing tank experiments with noisy and potentially non-linear input, it is crucial to run the small-scale turbine in a robust mode. A mathematical model of a PMDC motor dynamic system is derived incorporating a fuzzy logic controller. In addition, this drive control was validated experimentally. The experimental design is discussed in detail. The system performance was tested experimentally over a wide range of operating condition to validate the fuzzy logic control robustness and effectiveness. Also, it is shown that the speed of the PMDC motor was controlled by using this fuzzy logic controller. The speed tracking shows good agreement with the reference speed regardless of the load condition.
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- Award ID(s):
- 1809182
- PAR ID:
- 10475751
- Publisher / Repository:
- American Society of Mechanical Engineers
- Date Published:
- ISBN:
- 978-0-7918-8667-0
- Format(s):
- Medium: X
- Location:
- Columbus, Ohio, USA
- Sponsoring Org:
- National Science Foundation
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