Lead-acid batteries are still the cash cow in the market of energy storage systems. Use in vehicles will continue in the next years due to several advantages over competing products. Despite the high level of maturity of Lead-Acid Batteries (LABs), the Lead-Acid Battery (LAB) is with 40% by far the largest cause of short-term vehicle breakdowns. This is primarily not due to defective products, but rather to over-aged or deeply discharged batteries. The complex aging characteristics of lead-acid batteries do not allow the health status of a battery to be easily detected, which increases the probability of short-term failures. Our paper presents a solution of monitoring the current health status of a battery and discusses modeling opportunities in a cloud as a digital twin to predict breakdowns in the future. We present both, a Low Power Wide Area Network (LPWAN) based monitoring prototype and theory for state modeling and prediction.