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: IQInetics Technologies Inc.
• 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
• 起止时间: 2021-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2036023&HistoricalAwards=false
• 关键词: SBIR; Phase; innovative; calibration; software

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.

这个小企业创新研究（SBIR）第一阶段项目的更广泛的影响/商业潜力是通过开发一种软件解决方案来改善固有电动机的硬件问题。廉价的无刷直流（BLDC）电机具有电磁缺陷，限制了它们在工业和服务机器人应用中的采用。这些行业需要精确定位，先进的轨迹控制和平稳运行，这就需要高端电机，使用高质量的材料和复杂的硬件设计，最大限度地减少电磁缺陷。不幸的是，这增加了生产成本，使它们对许多应用程序来说过于昂贵。提出的解决方案将使电动机极其精确，高效，易于控制，同时保持低制造成本。低成本硬件和增强性能的校准软件的结合将为广泛的行业带来高端电机性能，这可能能够提高其设备的性能，同时节省高达90%的电机成本。第一个目标将是机器人市场，预计到2025年将达到1580亿美元，特别是无人机和工业领域，许多制造商必须平衡成本和性能。这项小型企业创新研究（SBIR）第一阶段项目旨在证明一种新的校准方法的技术可行性，以解决无刷直流（BLDC）电机的电磁和硬件缺陷。该技术基于1)在电机中嵌入位置传感器，收集生成电机电磁缺陷图所需的位置相关参数；2)专有算法，通过映射齿槽和相互转矩来改变输入电压/电流，消除各自转矩波动的负面影响；3)编码器误差校正，消除电机磁体的真实角位置与测量角位置之间的差异，改善电机校准和位置控制。本项目的研究活动可能会产生并验证一个最小可行的校准过程，该过程集成了所有描述的组件。校准软件在最大限度地减少低端无刷直流电机固有电磁缺陷影响和提高性能方面的能力，以及产生专门设计用于降低制造成本的创新硬件电机配置的可行性，将被评估。该项目的成功结果将证明校正软件在商业上的可行性。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。