Lithium-ion battery packs used in electric vehicles are highly vulnerable to short-circuit conditions, which can result in excessive heat generation, thermal instability, fire hazards, and long-term performance degradation. This research develops a proactive protection strategy based on embedded intelligence to detect and manage short-circuit risks at an early stage. The main objective is to improve operational safety by identifying abnormal electrical and thermal behaviors before they escalate into critical failures. The proposed methodology incorporates continuous real-time monitoring of essential battery parameters such as voltage, current, and temperature through integrated sensors connected to an embedded control unit. A rule-governed decision mechanism combined with predefined safety thresholds analyzes the acquired data and determines whether protective action is required. When irregular patterns associated with short-circuit events are detected, the system activates rapid isolation procedures to prevent further damage and contain fault propagation. Performance evaluation and comparison with traditional battery protection approaches indicate that the developed system achieves faster response times, improved detection accuracy, and enhanced overall safety reliability. The findings demonstrate that embedding intelligent decision logic directly within battery management architecture offers an effective and practical solution for minimizing short-circuit hazards in electric vehicle lithium-ion battery systems, thereby strengthening system durability and operational security.