2024年9月19日 · RealityCheck Motor 工具箱将 Renesas e² studio IDE 与我们基于云的 Reality AI Tools 机器学习环境相结合，为用户创建一个无缝的端到端工作流程，从数据收集到 AI 模型构建，再到紧凑、高效的嵌入式代码。

By integrating basic motor sizing rules with advanced optimization algorithm, the code optimizes motor design by minimizing the motor weight and maximizing efficiency under user-defined operating conditions. The code offers versatility, allowing users to automate specific motor or generator designs, explore various design spaces, or develop ...

2024年2月20日 · Through its unique combination of AI, ML and motor design ability, Monumo's proprietary technology runs around 10 million simulations per day to test potential iterations of the motor design. In turn, the platform can identify the optimal parameters for the specific use-case whether that is reducing cost, creating efficiencies or improving ...

2024年6月18日 · This review aims to comprehensively delineate the applications of AI within the realm of electric motors, specifically focusing into three pivotal stages: electric motors design, drive control, and health maintenance, covering a full …

EasiMotor Online是一个全面的设计和仿真优化工具，可实现一站式在线电机设计，电磁场有限元，振动和噪声分析等操作。 为了模拟电机在其他控制技术下的行为，其采用云计算资源快速确定电磁，并将其与实际运行控制结构合并。 链接: (https://online.easimotor.com/cm/jumpToEmOnlinePage.html) 利用人工智能和3D打印优化电机. Hyperganic软件平台自动设计高功能部件，结构，并在数码工厂通过工业3D打印，实现机器 …

2024年9月19日 · We have recently created a demonstration that shows how Renesas is helping make this possible. Our solution example flexes the muscles of the RA8T1 motor control MCU, showing independent control of two motors while simultaneously running multiple AI inference modules to detect anomalies of operation.

2024年3月6日 · ai可以实现电机的自适应控制，根据实时数据调整控制策略，使电机始终处于最佳运行状态。 AI可以快速准确地诊断电机故障，提高维修效率。 基于AI的预测性维护可以大大降低电机的故障率，提高使用寿命。

The paper shows a control system using artificial intelligence as an example of an induction motor with a frequency changer. Management is implemented using a fuzzy output controller. The optimal parameters of the fuzzy controller are determined.

2020年11月30日 · Design engineers want to introduce the power of AI to motors, for advanced motion control. For example, embedded algorithms could be used, based on information provided by intelligent sensors, to alleviate some common motor performance limitations.

2024年6月12日 · By applying AI, a CatBoost-based regression model was developed to estimate motor performance, including NVH and torque, based on motor design parameters, achieving impressive R-squared values of 0.94 - 0.99. Additionally, further key design predictors were analysed through SHAP.