The lab's battery research explores the impact of integrating heterogeneous battery cells into a battery pack. State (charge, temperature) and parameter (health) heterogeneity between battery cells within a battery pack is known to increase degradation of all cells and reduce pack capabilities. The lab's research uses physics-based battery cell models and control theory to determine fundamental trade-offs between balancing charge (which benefits short-term performance) and balancing capacity or temperature (which benefits long-term lifespan). This information is used to develop control algorithms which manage these trade-offs and balance heterogeneity only by shuttling charge. These control algorithms have been combined with computationally efficient state estimation schemes to determine internal states of the battery pack.

The lab's system-level research studies the behavior of systems with multi-domain components (e.g., electrical, thermal, mechanical) that potentially have timescale separation. A graphical decomposition methodology has been developed to yield a hierarchy of models useful for multi-level control algorithms. Application of these hierarchical control algorithms permits online trade-off decisions between tracking and constraint violation mitigation for systems such as an electric vehicle (EV) powertrain. A design framework has also been developed to support simultaneous component sizing and topology optimization for complex, multi-domain systems with reduced setup and solution times. Current research efforts combine these approaches for control co-design (CCD) with embedded, advanced control.

The lab's grid-level research explores the ability to integrate renewable resources into the electric grid through merging heterogeneous building energy system power demands together for demand response. The lab's research provides insights into how the electrical air conditioning (AC) system impacts energy stored with the building’s thermal capacitance for demand response. Analytic, characteristic damping ratios are determined to quantify the oscillations in aggregate power demanded by a population of heterogeneous building energy systems after a demand response event. These damping ratios can be used to perform population design, and develop demand response control algorithms.