  Latent thermal energy storage (TES) devices could enable advances in many
thermal management applications, including peak load shifting for reducing
energy demand and cost of HVAC or providing supplemental heat rejection in
transient thermal management systems. However, real-time feedback control of
such devices is currently limited by the absence of suitable state of charge
estimation techniques, given the nonlinearities associated with phase change
dynamics. In this paper we design and experimentally validate a state-dependent
Riccati equation (SDRE) filter for state of charge estimation in a phase change
material (PCM)-based TES device integrated into a single-phase thermal-fluid
loop. The advantage of the SDRE filter is that it does not require
linearization of the nonlinear finite-volume model; instead, it uses a linear
parameter-varying system model which can be quickly derived using graph-based
methods. We leverage graph-based methods to prove that the system model is
uniformly detectable, guaranteeing that the state estimates are bounded. Using
measurements from five thermocouples embedded in the PCM of the TES and two
thermocouples measuring the fluid temperature at the inlet and outlet of the
device, the state estimator uses a reduced-order finite-volume model to
determine the temperature distribution inside the PCM and in turn, the state of
charge of the device. We demonstrate the state estimator in simulation and on
experimental data collected from a thermal management system testbed to show
that the state estimation error converges near zero and remains bounded.
