Questar uses AI, predictive analytics to keep fleets on the road

Vehicle error codes and alerts are great for notifying drivers of problems that in many cases require immediate attention, but wouldn’t it be nice to get a heads-up a little bit sooner?

AI-based predictive analytics is becoming a valuable technology across industries where predictive maintenance can save money and labor time, while also ensuring operator safety and generally lowering everyone’s stress level. The automotive sector checks off all those boxes, and Questar Auto Technologies, a Tel Aviv-based company formed by November 2021 merger of auto technology firms Trafficlog and SafeRide Technologies, is looking to help.

Questar describes itself as a “predictive vehicle health company,” and offers a Vehicle Health Management (VHM) Platform that leverages AI and data collected from sensors to generate early warning of potential malfunctions in vehicles. This company last week announced that in a recent pilot program, its VHM platform was able to spot major malfunctions in 10% of the buses in a fleet operated by Israel’s Kavim Public Transportation company.

As a result of running Questar’s AI-based analytics software to monitor the health of its urban and intercity buses, Kavim was notified that while 90% of the tested buses were functioning properly, 10% of them had two major malfunctions that were not observable through any vehicles’ error codes, according to Questar. “The first malfunction was an issue with the vehicles’ exhaust systems due to an engine oil leak – a serious issue that was not reported by the engine controllers,” a Questar statement said. “The second malfunction was an issue with the exhaust systems’ particulate filters, which disrupted the pollutant burning cycle process that assures proper emission filtration.”

Gil Reiter, vice president of product management at Questar, told Fierce Electronics, “Most error codes are configured by OEMs to check for faults that require immediate attention, and they are based on simple rules. While in many cases, error codes appear after damage has already occurred, in this case, the problems were not yet apparent via the error codes. Questar’s unique solution is able to identify signs of a problem developing before it’s detected by the built-in error codes, minimizing the high cost associated with the fault repair.”

He added that most of Questar’s data is from sensors that are pre-installed by vehicle manufacturers, with sensor data collected through the CAN bus (which is the vehicle internal data communication network), but that Questar also leverages additional sensors that are installed in its telematics devices such as accelerometers and GPS.

Reiter said that Kavim has been using the VHM platform “for a long time,” and that Questar has many other ongoing pilot and proof-of-concept programs with companies across North America, Latin America, and Europe. “In many cases, once a successful pilot is complete, Questar works towards negotiating commercial deployments,” he said.

Reiter noted that many vehicles today, especially those used in fleets, undergo costly maintenance at fixed times as a preventative measure, even if they are in good condition. Still, fleet owners go on to spend hundreds of billions of dollars a year repairing problems that were not discovered until it was too late. On top of repair costs, unnecessary vehicle downtime comes with its own expense.

Questar said its field data shows that by using the VHM solution, fleet operators can realize a 30% reduction in costs on spare parts, a 10% reduction in fuel consumption, a 20% reduction in accidents, and up to 75% reduction in unnecessary downtime. Real-time health monitoring to optimize emission filtration and save fuel also makes fleets more environmentally sustainable, the company said.