The accurate state of health (SOH) estimation of Lithium-ion battery is one of the core issues faced by battery management systems. Considering that it is difficult to directly measure the battery capacity in practice, and the capacity regeneration problem always cause SOH estimation errors, a SOH estimation method of Lithium-ion battery is proposed based on incremental energy analysis and bidirectional gate recurrent unit ( BiGRU)-Dropout. The incremental energy curve is used to analyze the battery’ s degeneration characteristic, and the maximum peak height is extracted as a new health factor of battery SOH. Through the BiGRU network built by flip layer and gate recurrent unit layer, the mapping relationship between health factor and SOH is obtained. At the same time, Dropout mechanism network layer is added to prevent overfitting, and a SOH estimation model is established to accurate estimate the battery SOH. The results indicate that the proposed method can estimate battery SOH quickly and accurately under different charging rates.