EN3181 Battery Operation and Models

This course covers Lithium-ion battery system engineering and the necessary modeling, dynamic analysis, and optimization tools. After learning the basic operating principles of batteries, we will parameterize equivalent circuit models (resistance, capacitance, relaxation, and nonlinear polarization) from experimental data, and build battery digital twins to help us design battery systems for various mobile and stationary applications. We will cover ground vehicles (light/heavy duty), micro-mobility, and drones, along with an example from stationary (behind the meter) energy storage and a case study on power tools. The course will cover electrical and thermal equivalent circuit models for the normal, aged, and abnormal behavior of Lithium-ion batteries using empirical data-driven methods.

DoD Relevance: This course supports Department of War priorities in energy resilience, autonomous systems, and electrification of platforms. It equips students with technical competencies in battery modeling and diagnostics, systems thinking for pack integration, and decision-making for safe and efficient energy storage deployment.

Prerequisite

● Enrollment Prerequisite(s): o EN3180 – Battery Acquisition and Modeling o EC2100 - Circuit Analysis or similar course; instructor consent o Coursework or equivalent experience in calculus and differential equations ● Recommended Preparation: o EC2110 - Circuit Analysis II or similar course; instructor consent o Undergraduate-level physics, mechanical or electrical engineering recommended; familiarity with basic differential equations, electric circuits and heat transfer is expected.

Lecture Hours

Lab Hours

Course Learning Outcomes

Analyze Battery Energy and Power Capabilities

Students will calculate and interpret open circuit potentials at the electrode and cell level and explain how these relate to battery energy and power density.

DoW Alignment:

Technical Competence: Demonstrates understanding of electrochemical principles.
Critical Thinking: Applies analytical reasoning to energy/power tradeoffs.

Model Battery Behavior Using Empirical Techniques

Students will construct and evaluate equivalent circuit models of batteries, incorporating capacity, C-rate effects, and state-of-charge estimation to predict terminal voltage behavior.

DoW Alignment:

Systems Thinking: Models battery systems as dynamic components in larger platforms.
Technical Competence: Applies empirical modeling techniques to real-world battery behavior.

Design Battery Packs for Operational Applications

Students will size battery packs for drones, buildings, and BESS systems by selecting appropriate series/parallel configurations to meet energy, power, and range requirements.

DoW Alignment:

Operational Relevance: Size battery packs based on application requirements.
Problem Solving: Applies design principles to diverse operational contexts.

Assess Battery Degradation and Estimate State of Health

Students will analyze degradation mechanisms such as capacity fade and power loss, apply empirical models to estimate battery health, and evaluate pack inhomogeneity effects.

DoW Alignment:

Technical Competence: Understands degradation physics and data-driven modeling.
Systems Thinking: Evaluates health across heterogeneous battery packs.

Evaluate Battery Management Systems and Safety Protocols

Students will assess BMS hardware and balancing strategies, explain fast charging protocols, and identify safety risks including thermal runaway, venting, and abuse conditions, proposing appropriate sensing and diagnostic solutions.

DoW Alignment:

Communication and Decision-Making: Synthesizes technical data to inform condition-based maintenance or replacement.
Operational Relevance: Applies BMS and safety knowledge to improve battery utilization.