PhD in AI-Driven Battery Intelligence for Advanced Battery Management Systems in Electric Vehicles
Amrita Vishwa Vidyapeetham is inviting applications for a PhD opportunity in
AI-Driven Battery Intelligence for Advanced Battery Management Systems (BMS) in Electric Vehicles
.
The research is centered on developing next-generation intelligent BMS using
Artificial Intelligence
,
Machine Learning
,
Embedded Systems
, and
Physics-Informed Modeling
. The project aims to build robust algorithms for estimating and predicting key battery states such as
State of Charge (SoC)
,
State of Health (SoH)
,
State of Power (SoP)
, and
Remaining Useful Life (RUL)
.
Research themes include battery modeling, AI-driven analytics, embedded implementation, experimental validation, battery fault diagnosis and prognostics, thermal modeling, safety prediction, and electric vehicle energy management. A major emphasis is on hybrid AI-physics models that combine electrochemical battery behavior with data-driven learning for interpretability and strong predictive performance.
The work will involve simulation, hardware-based testing, and implementation on embedded platforms, with the goal of producing real-world intelligent battery monitoring and control solutions for future electric mobility and energy storage systems.
Funding
includes a fellowship of ₹30,000–₹40,000 per month, with enhanced opportunities up to ₹55,000 per month. Additional support is mentioned for research infrastructure (up to ₹10 Lakhs), publication support (up to ₹6 Lakhs), and international collaboration/conference travel.
Eligibility highlights
: candidates with strong analytical skills, curiosity for research, and interest in battery technologies, AI/ML, and sustainable mobility systems are especially welcome. The post does not specify a deadline, and no language-test waiver or fee waiver is mentioned.
How to apply
: use the Amrita admissions portal link provided in the post. Register, complete personal information, pay the application fee, and finish the remaining application steps before interview/test. International applicants should use the international admissions portal.
