%202%20(1).png)
The electrification of heavy transport, especially trucks and buses, introduces a new category of operational risk centered on lithium-ion battery systems. These batteries are essential for decarbonization, but they also bring new challenges that differ fundamentally from traditional mechanical or combustion systems.
For insurance companies, understanding how these batteries fail, and how such failures can be predicted or prevented, is key to setting fair premiums, assessing liability, and designing modern risk-based products.
Modern lithium-ion batteries achieve high energy density by using reactive materials and minimizing safety margins. This improves range and cost, but when something goes wrong, the stored energy can be released violently. Battery fires differ from fuel fires: once they start, they can feed themselves with oxygen generated from the battery’s own materials, making them very difficult to extinguish.
Although incidents remain rare, their impact is often catastrophic, resulting in total vehicle loss, damage to depots, and the release of toxic gases. Past examples in both grid storage and electric vehicles have shown that even experienced manufacturers can face serious failures with major financial and reputational consequences.
Battery failures can originate from several layers within the system:
In large battery packs, a particular concern is thermal propagation: when one overheated cell triggers its neighbors in a chain reaction, leading to complete system failure.
Battery Management Systems (BMS) play a central role in supervising cell voltage, temperature, and current. However, they have limited visibility: each BMS only monitors its own pack, has restricted computing power, and often lacks historical context or cross-vehicle comparison. These systems are designed to react to faults, not anticipate them.
Passive safety measures like fuses, vents, and fireproof housings are important, but they cannot prevent failures once they begin. Once a thermal event is underway, containment rather than prevention becomes the only option.
A new approach called predictive diagnostics adds a proactive layer of protection. By analyzing continuous data streams from the BMS in the cloud, predictive algorithms can detect early warning signs, such as abnormal voltage drift, rising impedance, or miscalibrated sensors, weeks or months before a serious failure occurs.
These systems flag issues in two stages:
By aggregating data from thousands of similar packs, predictive diagnostics can recognize recurring fault patterns and establish benchmarks across vehicle types and suppliers. Interestingly, we see more and more insurance companies make independent battery monitoring, often linked to central monitoring stations (CMS) mandatory.
When predictive data is unavailable or limited, often due to manufacturer restrictions, off-gas detection serves as a powerful supplementary safety measure. Independent testing by FM Global has shown that off-gas detectors can reliably identify the release of electrolyte vapors 5 to 20 minutes before thermal runaway begins.
This early-warning capability offers critical lead time to stop charging, isolate the vehicle, and protect surrounding assets. Off-gas detection is already used in battery energy storage systems and data centers, and it holds strong potential in depot environments where vehicles are charged in close proximity.
While not a substitute for full predictive diagnostics, off-gas detection strengthens overall risk mitigation. It adds redundancy to safety protocols and provides valuable insight when access to real-time battery data is not available.
While not a substitute for full predictive analytics, off-gas detectors can add an extra layer of protection, especially in enclosed environments like depots and charging stations. FM Global's research has shown that, in certain scenarios, prompt action taken after off-gas detection can prevent thermal runaway entirely.
Detection alone is not enough, response is essential. Both predictive alerts and off-gas warnings must trigger predefined safety procedures and immediate responses from a dedicated safety operator. These may include halting the charging process, isolating the affected vehicle, or relocating nearby vehicles to prevent the risk of thermal propagation.
If the risk of thermal runaway is detected, timely intervention is critical. Not only to prevent the incident but also to limit damage should it occur. It is essential that these emergency procedures are predefined, available, and regularly rehearsed, comparable to fire drills, so that all personnel know how to respond quickly and effectively when predictive alerts are issued.
Despite the benefits of predictive diagnostics, a major barrier remains: limited access to battery data. Many manufacturers restrict access to BMS data, preventing fleet operators and insurers from using advanced diagnostics to their full potential.
To enable effective monitoring and early intervention, data-sharing agreements must be negotiated during vehicle acquisition. This ensures that operational data is accessible throughout the lifecycle of the fleet, enabling both preventative maintenance and informed incident analysis. At Jump, we strongly recommend speaking with your insurance company before signing any purchase agreements.
Without this access, fleets are left to rely on incomplete information or secondary measures. In such cases, technologies like off-gas detection can serve as a practical, though more limited, safety layer, helping to mitigate risk when predictive diagnostics cannot be fully implemented.
Predictive diagnostics create new opportunities for insurers:
This transforms batteries from black boxes, high-risk components into transparent, data-rich assets.
For insurers, the rise of electric trucks and buses presents both new challenges and new opportunities. With modern battery systems now generating real-time operational data, it is possible to move beyond reactive approaches and adopt continuous, data-driven risk monitoring.
Fleets that use predictive diagnostics and ensure access to operational data can identify risks early, reduce the likelihood of serious incidents, and demonstrate stronger control over battery safety. This positions them to benefit from lower insurance costs, improved reliability, and greater trust from insurers.
