Modular multilevel converters (MMC) experience notable capacitor voltage ripple under low-speed, high-torque operating conditions. While high-frequency injection methods can mitigate the ripple, they can intensify device current stress, losses, and overmodulation risks. Furthermore, current parameter optimization strategies lack dynamic adaptability across all operating conditions. This paper proposes a multi-constrained adaptive optimization strategy for high-frequency injection parameters. First, a reference parameter table was generated using a variable-step gradient descent algorithm based on system characteristics and steady-state models, minimizing injected current while satisfying both capacitor voltage ripple and modulation wave amplitude constraints. Second, an online adaptive correction mechanism was designed to dynamically adjust injection parameters through real-time acquisition of capacitor voltage ripple and modulation information, compensating for parameter deviations and operational condition variations. This hierarchical architecture integrated offline global optimization with online local refinement. Simulation and experimental results confirm that the proposed strategy maintains voltage ripple suppression capability while significantly reducing high-frequency circulating currents, demonstrating dynamic tracking capability for optimization objectives.