The Holy Grail of Vehicle Quality: Using Connected Vehicle Data for Recall Cost Reductions

Yoni Zarruk

Vehicle Researcher

January 22, 2025

The recent recall of approximately nearly 200,000 plug-in hybrid electric vehicles of a global OEM has once again shone a spotlight on the challenges facing the automotive industry as it transitions to electrification. The recall, which addresses a defect in high-voltage batteries that could fail internally and lead to vehicle fires, serves as a stark reminder of the potential safety risks inherent in advanced vehicle technologies. 

While the OEM acted decisively by issuing a recall and advising owners to park their vehicles outside and away from structures, the incident raises critical questions: could the issue have been identified earlier? Could costly recalls and safety risks have been mitigated with more proactive measures?

Nearly 200,000 Vehicles Impacted by Battery Failure

High-voltage batteries are pivotal to the performance and safety of electric and hybrid vehicles, forming the foundation of clean, efficient transportation. Their complex design and operation demand meticulous engineering and continuous monitoring to maintain reliability. However, when issues occur—such as in this recent recall—the impact can be far-reaching, including safety hazards, diminished customer trust and satisfaction, and considerable financial and reputational repercussions.

A primary factor behind this recall was the defective cell separator material, which heightened the risk of thermal runaway and battery fires. In response, automakers took proactive steps by deploying a software update to the battery management system (BMS). This update optimized charging and discharging parameters to alleviate stress on the cells, minimize potential failures, and enhance safety as an interim solution while the faulty components were being replaced.

The traditional approach to identifying such issues often relies on patterns of warranty claims, service reports, and customer complaints—data sources that become actionable only after problems have occurred on a noticeable scale. This reactive process not only delays resolution but also exposes automakers to potentially devastating consequences, including safety risks and regulatory scrutiny.

Connected Vehicle Data is a Gamechanger

Connected vehicles generate vast amounts of data, from battery performance metrics to environmental conditions and driving behavior. By leveraging this data in near real-time, automakers can detect early warning signs of potential issues before they escalate.

Here’s how:

  1. Real-Time Monitoring: Continuously monitor individual cell voltages, temperatures, and currents, along with overall battery pack voltage, current, and temperature during charging and driving. This comprehensive approach ensures early detection of issues such as cell imbalances, overheating, voltage irregularities, or rapid degradation. By providing real-time insights, active monitoring enables automakers to identify and address potential problems before they escalate, ensuring the reliability and safety of high-voltage battery systems.
  2. Root-Cause Analysis and Virtual Investigations: When an anomaly is detected, after-sales quality teams can leverage advanced machine learning and AI modules to rapidly analyze patterns across the entire fleet to identify commonalities, such as specific manufacturing batches, environmental conditions, or usage scenarios. This enables a targeted investigation and faster analysis of the potential root cause.
  3. Proactive Software-Driven Mitigation: Armed with insights from connected vehicle data, automakers can issue over-the-air (OTA) software updates to adjust battery management system parameters, reducing the risk of failure. In cases where hardware intervention is necessary, recalls can be more precise and less disruptive.
  4. Cost Savings and Long-Term Customer Satisfaction: By addressing issues early and accurately, automakers can avoid the cascading costs of large-scale recalls, legal liabilities, and reputational damage. Early detection also enhances customer trust by demonstrating a proactive commitment to safety.

Advanced AI Supports a Proactive and Shift-Left Approach to Vehicle Quality

This recent recall case study underscores the urgent need for a paradigm shift in how automakers approach quality and safety in the era of electrification. By leveraging advanced AI-based analytics, automakers can transition to a model of data-driven quality investigations, identifying and addressing potential issues before they escalate, ensuring both safety and operational excellence in the era of electrification.

At the forefront of this transformation is the integration of AI-powered platforms designed to monitor, analyze, and act on data from millions of connected vehicles. These platforms empower automakers to transition from reactive problem-solving to proactive risk management, ensuring that issues like those seen in this case study are identified and mitigated effectively.

AI not only supports early detection of quality issues and their impact, but also enables a shift-left approach, which focuses on improving quality across the entire vehicle lifecycle. By detecting quality issues early (minimum Months-In-Service) and pinpointing their root cause, AI empowers OEMs to revise Software Bill of Materials (SBOM) and Hardware Bill of Materials (HBOM) during the production phase, long before vehicles hit the road. This strategy enhances the production process while mitigating risks, reduces future recall costs, and ensures vehicles meet the highest standards of safety and reliability.

In recent months, the automotive industry has been under increasing pressure to balance cost savings with maintaining customer satisfaction. Vehicle quality is a critical factor in achieving this balance. However, OEMs often address cost pressures by reducing investments in talent or technology—both essential for sustainable, long-term growth. By leveraging connected vehicle data and AI, the industry can not only avoid expensive recalls but also create a safer and more reliable future for consumers.

The question is no longer whether these technologies should be adopted but how quickly automakers can integrate them into their operations. The stakes are high, and the time to act is now.

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