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SBIR Phase I: An innovative calibration software to suppress torque ripple and improve performance of electric motors.

SBIR Phase I: An innovative calibration software to suppress torque ripple and improve performance of electric motors.
SBIR 第一阶段:一款创新的校准软件,用于抑制扭矩脉动并提高电动机的性能。
批准号:
2036023
负责人:
Matthew Piccoli
金额:
$25.52万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2021
资助国家:
美国
项目状态:
已结题
起止时间:
2021-01-01 至 2021-12-31

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中文摘要
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英文摘要
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to improve the market by developing a software solution to intrinsic electric motors’ hardware problems. Inexpensive Brushless Direct Current (BLDC) motors have electromagnetic flaws that limit their adoption in industrial and service robotic applications. These industries require precise positioning, advanced trajectory control, and smooth operation which require high-end motors that minimize electromagnetic flaws using high-quality materials and complex hardware designs. Unfortunately, this increases production costs, making them prohibitively expensive for many applications. The proposed solution will make electric motors extremely precise, efficient, and easily controllable while keeping manufacturing costs low. The combination of low-cost hardware and performance-enhancing calibration software will bring high-end motor performance to a wide range of industries, which may be able to improve the performance of their devices while saving up to 90% on motor costs. The first target will be the Robotic Market, expected to reach $158 billion by 2025, in particular the drone and industrial segments, where many manufacturers must balance cost and performance. This Small Business Innovation Research (SBIR) Phase I project seeks to prove the technical feasibility of a new calibration approach to solving electromagnetic and hardware flaws in brushless direct current (BLDC) motors. The technology is based on 1) embedded position sensors in the motor to collect the position-dependent parameters necessary to generate maps of motors’ electromagnetic flaws; 2) proprietary algorithms that map cogging and mutual torque to vary the input voltage/current, eliminating the negative impact of the respective torque ripple; 3) encoder error correction to eliminate the discrepancies between the true and the measured angular positions of the motor magnets, improving motor calibration and position control. The research activities in this project may result in the generation and validation of a minimum viable calibration process that integrates all the described components. The ability of the calibration software to minimize the impact of the inherent electromagnetic flaws in low-end BLDC motors and enhance performance will be assessed together with the feasibility of generating an innovative hardware motor configuration specifically designed to reduce manufacturing costs. The successful outcome of this project will demonstrate the commercial feasibility of the calibration software.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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SBIR Phase II: An innovative calibration software to suppress torque ripple and improve performance of electric motors.
  • 批准号:
    2233023
  • 项目类别:
    Cooperative Agreement
  • 资助金额:
    $98.99万
  • 财政年份:
    2023
  • 负责人:
    Matthew Piccoli
  • 依托单位:
国内基金
海外基金
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  • 项目类别:
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  • 资助金额:
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  • 依托单位:
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  • 批准号:
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  • 项目类别:
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  • 资助金额:
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  • 批准年份:
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  • 负责人:
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  • 依托单位:
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  • 项目类别:
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  • 资助金额:
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  • 批准年份:
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  • 负责人:
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