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.

这项小型企业创新研究（SBIR）I阶段项目的更广泛的影响/商业潜力是通过开发软件解决方案来改善市场来改善市场，以固有电动机的硬件问题。廉价的无刷直流电流（BLDC）电动机具有电子缺陷，可限制其在工业和服务机器人应用中的采用。这些行业需要精确的定位，高级轨迹控制和平稳的操作，这需要使用高质量材料和复杂的硬件设计来最大程度地减少电子缺陷的高端电动机。不幸的是，这增加了生产成本，使其适合许多应用程序。提出的解决方案将使电动机非常精确，高效且易于控制，同时使制造成本较低。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运动性能，这可能能够改善其设备的性能，同时节省90％的汽车成本。第一个目标是机器人市场，预计到2025年将达到1580亿美元，尤其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）I阶段项目旨在证明一种新的校准方法的技术可行性来解决无刷直流电（BLDC）电动机中的电子和硬件缺陷。该技术基于1）电动机中的嵌入位置传感器，以收集与位置相关的参数，以生成电动机电子缺陷的地图； 2）映射齿条和相互扭矩以改变输入电压/电流的专有算法，从而消除了相对扭矩波纹的负面影响； 3）编码器误差校正以消除电动机磁体的真实角度和测得的角位置之间的差异，从而改善电动机校准和位置控制。该项目中的研究活动可能会导致产生和验证最低可行的校准过程，从而整合了所有描述的组件。将评估校准软件在低端BLDC电动机中继承电子缺陷的影响以及增强性能的能力，并将评估具有创新的硬件电动机配置的可行性，以降低制造成本。该项目的成功结果将证明校准软件的商业可行性。该奖项反映了NSF的法定任务，并使用基金会的知识分子优点和更广泛的影响评估标准，被视为通过评估而被视为珍贵的支持。