This chapter proposes an integrated state-power control framework to coordinate the multiple state estimation and real-time power control. Firstly, two lightweight state estimation models are proposed: a swaying-coupled joint state estimation (JSE) method, which reduces SOC and SOH estimation errors by up to 97.72% and 80.6%, respectively; and a temperature-coupled improved extended Kalman filter (I-EKF) method, achieving an average SOC estimation error of 0.676% across temperatures. Furthermore, adaptive power control strategies are developed, including a hierarchical power allocation strategy to minimize invalid energy flows, a model-free adaptive learning control ensuring finite-time error convergence, and emission-aware/health-aware controllers optimizing fuel efficiency and battery health. These strategies integrate dynamic SOP constraints to prevent overloading and compensate for power deficits. The proposed framework balances state estimation and power control time scales, enhancing LiBs’ marine environmental adaptability and enabling safe, efficient shipboard energy management.