Challenges and Best Practices in Deploying Liquid-to-Air Sidecar CDUs for AI Data Centers

Abstract The rapid growth of AI workloads has pushed rack power densities to unprecedented levels, testing the limits of legacy air-cooled data centers. Liquid-to-air (L2A) sidecar coolant distribution units (CDUs) have emerged as a practical and cost-effective solution for enabling rack deployments exceeding 125 kW without requiring major infrastructure changes. However, their scalability and reliability in real-world environments remain constrained by issues like airflow recirculation, sensor drift, control-loop instability, and slow redundancy activation. This study presents a systematic experimental investigation of L2A CDU performance under high-load conditions. Key operational challenges, including air leakage, flow sensor drift, fan speed oscillations, and delayed pump and fan failover, were identified and addressed. Targeted solutions such as ultrasonic flow sensing, predictive fan control algorithms, and dual-active pump configurations were implemented and validated. The results provide a practical roadmap for reducing deployment risks and improving system resilience. As AI data centers continue to scale toward megawatt-class rack power levels, this work highlights the critical factors to consider when transitioning from hybrid cooling solutions to next-generation liquid-focused thermal architectures.