  Technological advancements like the Internet of Things (IoT) have facilitated
data exchange across various platforms. This data exchange across various
platforms has transformed the traditional battery system into a cyber physical
system. Such connectivity makes modern cyber physical battery systems
vulnerable to cyber threats where a cyber attacker can manipulate sensing and
actuation signals to bring the battery system into an unsafe operating
condition. Hence, it is essential to build resilience in modern cyber physical
battery systems (CPBS) under cyber attacks. The first step of building such
resilience is to analyze potential adversarial behavior, that is, how the
adversaries can inject attacks into the battery systems. However, it has been
found that in this under-explored area of battery cyber physical security, such
an adversarial threat model has not been studied in a systematic manner. In
this study, we address this gap and explore adversarial attack generation
policies based on optimal control framework. The framework is developed by
performing theoretical analysis, which is subsequently supported by evaluation
with experimental data generated from a commercial battery cell.
