**1. Introduction**

Well-known greenhouse gas (GHG) emissions, due to extensive use of diesel and gasoline, threaten our environment [1]. A large amount of CO2 from transportation is gradually decreasing [2,3]. Meanwhile, electric vehicles (EVs) have been identified as being a key technology in reducing emissions and energy consumption in the transport sector [4]. Most countries are stepping up the introduction of electric vehicles, and are trying to progressively replace traditional fuel vehicles with EVs. However, with the rapidly increasing popularity of various EVs, the demand for lithium-ion batteries (LIBs) increases annually [5,6]. Sales of pure electric cars rose by nearly 14% in 2018 compared to 2017, while hybrid and plug-in hybrid sales rose by more than 20%. Now, more than 1.15 million EVs are on the roads today in the world [7]. Consequently, the quantity of wasted LIBs is also quickly increasing [8]. However, wasted battery packs are still available for energy balancing in thermal power plants, due to their residual electrical capacity [9]. Reuse of LIBs has become crucial in recent years [10], since renewable energy sources such as solar energy and wind energy are intermittent in nature. They have to keep continuous and reliable supply [11–13]. One of the best ways of stabling these renewable resources is to be stored in batteries. Among them, LIB is widely accepted due to its high energy density, long lifespan, and high efficiency [8,14,15]. However, the lifecycles of reused LIBs (RLIBs) become short, because the geometrical structure of the battery is possibly damaged by cycling

use [16]. Therefore, an effective battery management system (BMS) for RLIB is compulsory, so that batteries can operate safely and reliably, preventing any physical damages and cell unbalancing [17]. Besides this, the state of charge (SOC) in BMS is considered as one of the critical and important basic parameters [14,18–20], which indicates how much remaining capacity is left inside a battery. Accurate estimation of SOC not only helps to provide information about the charge current and remaining performance of the battery, but also gives assurance of reliable and safe operation of the battery. However, the performance of the battery is highly affected by aging, temperature variation, and charge/discharge cycles, which make the task of estimating accurate SOC very challenging [21]. Therefore, we apply an adaptive control algorithm [16] for online estimation of key parameters, which are known as simple and easy to implement in BMS. For reused batteries, online estimations of electrochemical related parameters, such as internal resistances, are capable of real-time monitoring of the safety of reused batteries, rather than normal battery management systems for new batteries. Besides this, for prolonging a RLIB's life, one ultracapacitor (UC) is connected and controlled by BMS to share peak load power. One simple pulse-width modulation (PWM) module is adopted to adjust the duty ratio of RLIB. Verification of this battery management for RLIB is conducted by systematic testing on bench by monitoring online results of estimation. It is expected that this study will contribute to promoting the systematic reuse of wasted LIB in industry before the chemical method.
