TRIZ-AI™ : EV 배터리 라이프사이클 인텔리전스 플랫폼

Electric vehicle batteries degrade over years of use, but it has been difficult for drivers or companies to determine exactly when to replace them. Excessive use can lead to the risk of thermal runaway fires, and replacing them too early results in wasted costs and materials.

Existing BMS systems show a rough estimate of the battery's condition, but their prediction accuracy is low because they do not comprehensively consider various factors such as driving habits and charging patterns. In addition, transportation companies or leasing companies operating large numbers of vehicles also lack individual battery monitoring systems.

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TRIZ-AI collects all data from the Battery Management System (BMS), such as voltage, current, temperature, charge/discharge patterns, and driving habits, to the cloud via the vehicle's OBD-II port[59][60]. A deep learning model learns from this big data to accurately calculate the Remaining Useful Life (RUL) of each battery and even detect signs of thermal runaway (fire) early on[61][62].

For example, if it detects voltage imbalance between cells or abnormal heat generation patterns, it immediately issues warnings and recommends precision inspections, and provides users with health reports and operating guides[60][63]. In addition, it supports the battery data utilization ecosystem through API integration with insurance companies, vehicle control, and government systems (e.g., insurance premium discounts, automated recall target determination)[32].

It is currently in the practical application stage with a real-vehicle test of 6,000 units, which greatly improves battery life and driving safety[64].

Major customers include companies with a large number of electric vehicles (taxi/bus companies, logistics companies, etc.), insurance companies, and electric vehicle manufacturers/dealers. Individual owners can also use it in the form of an OBD device + subscription, but it is mainly expected to be introduced as a B2B/B2G (control center) model.

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As EV distribution increases, all electric vehicles worldwide become the target market. Service is possible without regional restrictions as long as vehicle compatibility is secured, and it can be expanded to all mobility using batteries, such as autonomous driving shuttles and E-mobility.

However, data access permission must be obtained from each automobile manufacturer, which requires standardization and cooperation. In the future, business expansion is expected to include residual value assessment of used batteries and secondary use marketplaces based on accumulated data.

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It was evaluated as a "comprehensive health checkup platform for the EV era" and attracted attention as a realistic solution due to the concreteness of the actual 6,000-unit test[64]. Analysts say that it is attracting great interest from the finished vehicle and insurance industries by addressing both driving safety and cost reduction.

On the other hand, the possibility of automobile manufacturers developing their own solutions is pointed out as a competitive factor, and how to establish a cooperative structure remains a challenge. In summary, the technical usefulness is very high and the market demand is clear, but cooperation with industry players will determine its success.