# Research on Equalization Strategy of Lithium Battery Pack Based on Multi-Layer Circuit
## 2 Related Work
The ant colony algorithm is used to solve the optimal equalization path, which reduces the flow of current and increases energy utilization due to the slow equalization speed of using a single inductance equalization circuit. Reference [19] used the push-pull converter to control the equalization current, and the equalization efficiency can reach 89.5% at most. However, when the voltage difference between the two batteries is large, the equalization current be becomes large too. Reference [31] proposed a multi-switch equalization circuit. For this circuit, an equalization strategy was proposed, which balances the charge-discharge state and the static state separately. The equalization paths are more diversified and reduce the energy loss, but the equalization speed is too slow when the static equalization is carried out. Reference [32] used battery SOC to control the duty cycle of the MOS transistor, although the equilibrium current and calorific value were reduced, there is still much room for improvement. Reference [33] proposed a switching equalization controller circuit, which can realize the simultaneous equalization of multiple batteries. However, when the battery voltage difference is too small, the equalization efficiency is low. When the battery voltage and the equalization current is too large, the battery life is shortened. Reference [34] proposed an adaptive model prediction method, which takes the energy loss and equalization time as the optimization conditions to realize the optimal SOC equalization control. Although the equalization speed is accelerated, the current is doubled, and the battery is greatly damaged. Reference [35] used fuzzy logic to control the equalization current, with temperature, internal resistance, and SOC as inputs and equalization current as output, so as to make the battery more balanced within the safe temperature range. However, this method is qualitative rather than quantitative. The current in the equalization process may be greater than the maximum allowable current. In large-scale applications, the base of fuzzy rules becomes very complex. Reference [36] only used the MOSFET switch to realize the equalization of the battery pack, which balances the charge state and discharge state separately \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Equalization Circuit** & **Cost** & **Equilibrium Speed** & **Equilibrium Current** \\ \hline Single inductor & Low & Low & Low \\ \hline Adjacent inductance equalization [21] & Medium/High & Medium & Medium/High \\ \hline Multi-layer inductor [22] & Medium/High & High & High \\ \hline Multi-winding transformer [23] & High & Medium & Medium \\ \hline Cuk converter [24] & Medium/High & Medium & Medium/High \\ \hline Single SC [25] & Low & Low & Low \\ \hline Modularized SC [26; 27] & Medium/High & High & High \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Equalization circuit performance comparison. and reduces the energy loss. However, it may lead to problems such as insufficient power supply or excessive discharge current of some batteries during the batteries' discharging. Reference [37] realized the safe charging of aged lithium batteries by using the MPC method. Compared with the traditional SOC control method, the battery pack SOC equalization is faster, the energy consumption is lower, and the over-equalization phenomenon can be avoided. However, the MPC-based equalization method is computationally complex and difficult to be applied on a large scale. Although the preceding strategies have produced good equalization outcomes, there are still flaws. When solving the battery equalization current, these solutions ignore the impact of the equalization current on the system. The battery current exceeds the permitted range during equalization, which can reduce battery life. In extreme circumstances, this can result in a rapid rise in battery temperature and possibly thermal runaway.