工厂与楼宇自动化

利用依托实时洞察与可靠运行的系统，实现运动控制、资产监测与设施安全保障。我们的解决方案为工厂与楼宇自动化提供连接、电源与传感能力。

电机驱动与电源控制

提供电源与控制技术，使电机在不同负载条件下实现高效驱动、转速调节与稳定运行。

智能电机控制
  • Intelligent BLDC/PMSM motor control
  • High-efficiency torque and speed control
  • Integrated safety and diagnostics
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Motor Control
Motor Control
智能电机控制
  • Intelligent BLDC/PMSM motor control
  • High-efficiency torque and speed control
  • Integrated safety and diagnostics
View related products

负载下的电机控制

能效要求提升与更严苛的运动控制需求，推动泵、风扇、伺服电机与压缩机等应用对更智能电机系统的需求。

E-Book

电机控制For Dummies

您将了解: 电机控制基础： 电机控制器如何工作 BLDC（无刷直流） 电机和PMS（永磁同步电机）的兴起 关于BLDC电机控制系统有我传感器电机之间的区别 电机控制换向和控制电机的算法 点击下载

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E-Book

电源管理基础傻瓜书

您将了解: 电源管理基础： 直流稳压器,线性稳压器和开关稳压器之间的区别 电源管理应用案例 如何在开关稳压器中管理EMI（电磁干扰）和噪声纹波 点击下载

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White Paper

无刷直流电机及其驱动器的设计挑战与注意事项

Generating rotary motion was one of the first experiments carried out with electricity in the 18th century – an 'electric whirl' was invented, actually an electrostatic reaction motor, but it was just seen as a novelty. Today, electric motors consume 53% of global electricity production, according to ‘4E Electric Motor Systems Annex' (EMSA) [1]. Another report by the International Energy Agency (IEA) states that typically 95% of a motor's lifecycle cost is electricity to power it and if users change to the most efficient motors and drives, by 2030, global electricity demand could be reduced by 24-42 TWh, representing 16-26 Gt reduction in CO2 emissions. All this is in a market worth nearly USD 142 billion, growing at an expected 6.4% CAGR according to market analysis in 2020 [2].

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White Paper

智能电源管理系统中的机器学习

Machine learning for MCU implementation (tiny ML) is a growing field that offers new and enhanced functionality for battery management and motor control. ML algorithms discover information and patterns in complex sensor data that can be used to optimize performance and improve understanding of overall system health. In addition to advances in tiny ML techniques, the availability of AutoML tools that automate the collection of data, training of ML algorithms, and generation and deployment of MCU firmware is on the rise. Such tools, combined with access to system on chip (SoC) sensor data, enable the development of ML-based solutions in today’s power management systems. This paper discusses the development of machine learning (ML) applications using Qorvo’s intelligent power management systems ICs. Qorvo's highly integrated power management SoCs combine Arm® Cortex® M0 and M4F MCUs with an analog front end with an array of sensors to enable smart control and monitoring functions.

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Video

Time for Timers: Part 1 - PPM Tutorial Video

In this tutorial video, Qorvo's Power Management Team reviews all the peripherals needed to drive a BLDC / PMSM motor. Learn all about PWM modulation techniques, timer peripherals and dead time generators.

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Video

Time for Timers: Part 2 - PPM Tutorial Video

In Part 2 of this tutorial video, Qorvo's Power Management Team shows real-world examples of the peripherals needed to drive a BLDC / PMSM motor. Using the PAC5523, this video details Pulse Width Modulation technics, timer peripherals, and dead-time generation.

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