Renesas Blog

瑞萨电子于11月2日在吉利汽车杭州湾研发中心举办技术交流活动，并与吉利团队分享了瑞萨在汽车电子领域的先进产品和解决方案。

In this blog, the RH850 Virtual Platform (VPF) function to improve the safety and quality of automotive software is introduced.

We will introduce a multi-device synchronous debug & trace tool (released in September 2022) that enables synchronized execution, break control, and acquisition of trace information for multiple SoCs and MCUs.

Software is becoming the new sensor. This shift in thinking opens the door to incorporating more complex, AI-based algorithms, rather than just simple condition thresholds.

Relying only on high-level descriptive statistics rather than time and frequency domains will miss anomalies, fail to detect signatures and sacrifice value that an implementation could potentially deliver.

Real-time streaming data must be carved into smaller windows for consideration by a machine learning model, how that stream is carved up can have an impact on model performance and power consumption.

As sensor and MCU costs decreased, an ever-increasing number of organizations have attempted to exploit this by adding sensor-driven embedded AI to their products.

The more sophisticated machine learning tools that are optimized for signal problems and embedded deployment can cut months, or even years, from an R&D cycle.

This post offers tips on collecting data from high-sample-rate sensors for use with machine learning.

Renesas released direct communication tool between customers and partners in Sep/2022. Customers can get high level solution proposal from R-Car Consortium partners to your problems and accelerate automotive development.