The exponential growth of the electric vehicle (EV) industry, driven by decarbonization goals and energy transition policies, has intensified the need for sustainable and transparent supply chains. Lithium-ion batteries (LIBs), the cornerstone of EVs, pose complex life cycle challenges related to ethical sourcing, environmental degradation, traceability gaps, and inefficient end-of-life (EOL) management. Addressing these multifaceted issues requires an integrated technological approach. This study proposes a unified framework leveraging Digital Product Passports (DPPs) and blockchain technology to enable real-time, tamper-proof tracking of battery materials, components, and performance metrics throughout their lifecycle.The paper further integrates machine learning, with a focus on reinforcement learning (RL), to optimize logistics and predictive maintenance based on dynamic supply chain data. To ensure privacy and regulatory compliance in data sharing, the framework incorporates zkSNARKs—a zero-knowledge proof system that preserves confidentiality while maintaining verifiability across distributed networks. This triadic approach promotes lifecycle transparency, supports circular economy goals through efficient material reuse and recycling, and reduces the total cost of ownership (TCO) for EV stakeholders.The proposed solution addresses critical industry challenges—such as counterfeit components, low recycling efficiency, and supply chain opacity—while offering scalable applications in adjacent sectors like consumer electronics and renewable energy. The integration of DPPs, blockchain, and AI-based optimization establishes a resilient, interoperable infrastructure that enables enhanced sourcing, sustainability, and collaborative innovation in the evolving EV ecosystem.