Nissan Motor Co. and Canadian tech firm Acerta Analytic Solutions are collaborating on developing an innovative artificial intelligence (AI) tool designed to anticipate engine component failures.
The new failure prediction analytics solution pulls data from the vehicle’s electronic control unit. It uses machine learning algorithms to forecast potential component failures and estimate the remaining distance the vehicle can cover before warning the driver.
Kazuhiro Doi, vice president of Nissan’s research division, expressed enthusiasm for the ongoing partnership during the demonstration event.
“Nissan recognizes the strength in Ontario’s thriving automotive ecosystem and expertise in AI and manufacturing. We worked with Acerta to accelerate the development of this technology for our vehicles. We’re excited to continue our partnership,” said Doi.
The $1.36M CAD project was made possible thanks to support from the Government of Ontario through the Ontario Vehicle Innovation Network (OVIN) and other industry contributors.
Predictive Intelligence for Breakdown Probability
Predictive maintenance solutions utilizing onboard sensors, big data, and AI are poised to bring substantial advantages to vehicle owners.
Through the power of predictive analytics, Nissan aims to proactively identify potential engine component failures before they escalate into major issues. This forward-looking approach not only enhances customer satisfaction by minimizing unexpected breakdowns but also translates to significant financial savings and increased safety for vehicle owners.
Issues Covered by Predictive Technology
Nissan’s initial emphasis is on addressing fuel injection failures, primarily because fuel injectors play a pivotal role in internal combustion engine-equipped vehicles. Prior to the incorporation of AI, detecting these failures in advance proved to be an exceedingly challenging task.
Although the current system’s scope is limited to assessing fuel injectors, there are intentions to broaden its application. This expansion will include areas such as internal combustion engine power trains, electric vehicle components, and, notably, advanced driver assistance systems, which aim to enhance collision avoidance.
Ultimately, predictive maintenance, grounded in cutting-edge technologies, machine learning, and AI, presents promising advantages for vehicle owners and manufacturers.
