Early Detection of Failing Lead-Acid Automotive Batteries Using the Detrended Cross-Correlation Analysis Coefficient  
[PERSON]  
1 Departamento de Modelagem Computacional, Universidade SENAI CIMATEC,  
Salvador 41650-010, BA, Brazil; [EMAIL_ADDRESS] (H.B.A.B.P); [EMAIL_ADDRESS] (R.L.S.M. ; [EMAIL_ADDRESS] (M.A.M.)) [PERSON]  
2 Stoneridge Electronics AB, Gustav IIIs Boulevard 26, 169 73 Solna, Sweden; [EMAIL_ADDRESS] 2  
[PERSON]  
13 Departamento de Educacao, Universidade do Estado da Bahia--UNEB, Salvador 41150-000, BA, Brazil 3  
[PERSON]  
14 Departamento de Ciencias Exatas e da Terra, Universidade do Estado da Bahia--UNEB,  
Alagonihas 48000-000, BA, Brazil 4  
[PERSON]  
15 Departamento de Ciencias Exatas e da Terra, Universidade do Estado da Bahia--UNEB, Salvador 41150-000, BA, Brazil 5  
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There have been few changes in automotive lead-acid batteries technology over the past 90 years. With respect to design and manufacturing process technologies, batteries are expected to have an average lifespan ranging from 2 to 7 years (depending on climatic conditions), reliability and robustness, cold start capacity, and the ability to meet all these requirements with minimal material consumption, weight, and cost [2]. Despite having a relatively low energy density, only 30 to 40% of the conceptual limit when compared to 90% for lithium-ion batteries, lead-acid batteries are advantageous due to their use of abundant, nonflammable, and low-cost materials, and water-based electrolyte. Additionally, manufacturing practices with a 99% recycling rate significantly minimize their environmental impact [3, 4]. If the starter motor does not function properly, one of the possible causes is malfunction of the lead-acid battery. The battery undergoes wear over time, until a moment when it ceases to serve its primary function [5]. To monitor the state of a battery, many automakers use sensors in close proximity. This sensor setup is known as the Battery Monitor Sensor (BMS) [1], which typically monitors current, temperature, and battery voltage. In some applications, the BMS is positioned directly on the negative terminal of the battery and communicates through a Local Interconnect Network protocol with an Engine Control Module, in some cases with the Body Control Module (BCM) of the vehicle. An automotive battery is a complex nonlinear electrochemical process for which behavior analysis is needed to determine its usage conditions, such as the State of Charge (SOC) and State of Health (SOH). From this battery data acquisition by the BMS and sharing with the BCM, several control strategies have been developed and implemented, such as inferring the SOC of the battery from a combination of the voltage and the delta of the current entering and leaving the battery. The SOH is calculated as the ratio of the actual cell capacity resistance to its initial value [6, 7, 8]  
Nowadays, innovations and cutting-edge advancements in renewable energy conversion are transforming global energy systems, such as hybrid electric vehicles (HEVs) and renewable electricity generation, to significantly decrease reliance on fossil fuels [9]. Despite the widespread adoption of lithium-ion batteries in HEVs, lead-acid batteries have remained the predominant electrochemical power source for medium-to-large energy storage applications since their development [10]. Lead-acid batteries are required to operate under partial state of charge conditions for renewable energy storage and HEV applications, but a specific failure mode known as sulfation degrades their capacity and performance [11]. To address this challenge, a new technology called Lead-Carbon Batteries has emerged, incorporating functional carbon additives into the negative active material to raise the performance of traditional lead-acid batteries [12].