Renesas Electronics introduces an e-AI solution for motor fault detection that greatly simplifies household appliance maintenance

     Renesas Electronics has announced the launch of an e-AI fault detection solution for motor control in home appliances. The solution uses Renesas Electronics RX66T 32-bit microcontroller (MCU), based on embedded artificial intelligence (e-AI), which can detect the failure of refrigerators, air conditioners, washing machines and other home appliances due to motor abnormalities. Motor control and E-AI-based anomaly detection can be achieved with a single MCU without the need for additional sensors by directly utilizing property data that can show motor status, such as current or speed.

     The general motor working condition monitoring is carried out when it is running, and the fault detection is real-time. Home appliances usually fail when the motor runs abnormally. With fault detection based on e-AI and for motor control, the results of the detection can not only be used to trigger an alarm when a fault occurs, but also for preventive maintenance - for example, e-AI can predict when repairs and maintenance will be needed, and pinpoint the exact location of the fault. The new ability to predict product failures before they occur will effectively improve maintenance efficiency and product safety for appliance manufacturers.

     Thanks to a high-performance RX66T MCU, the e-AI fault detection solution for home appliance motor control can control up to four motors. Current washing machines usually contain three motors: one for rotating the washing bucket, one for driving the water circulation pump, and one for driving the drying fan. The e-AI fault detection solution controls all three motors with a single RX66T chip, while monitoring the operation of all three motors and troubleshooting.

     This new solution uses Renesas Electronic Motor Control Evaluation System and RX66T CPU card. The hardware is combined with a set of sample program files running on the RX66T MCU, and a set of GUI tools capable of collecting and analyzing data indicating motor status attributes. To detect faults, it is necessary to understand the motor characteristics under normal conditions. By using GUI tools, system engineers can immediately start developing and optimizing AI learning and fault detection capabilities. Once the AI modeling is completed, mature AI models can be easily imported into the RX66T in the e-AI development environment (composed of e-AI Translator, e-AI Checker and e-AI Importer tools).

     Toru Moriya, Vice President, Home Business Unit, Renesas Electronics Industrial Solutions, said, "Renesas Electronics has leveraged its extensive and specialized knowledge in the development of home appliance application solutions to discover faults affecting the entire system based on the detection of abnormal motor operation. In the past, even in the case of a failure of the motor itself, it was difficult to determine the source of the fault and determine whether an anomaly occurred in the motor or inverter circuit. This new solution can quickly identify the location of the fault, significantly reducing the maintenance burden on customers."