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Model Predictive Control of Residential Baseboard Heaters with Distributed System Architecture

Burger, Eric M.
Perez, Hector E.
Moura, Scott J.
2014

Typical residential HVAC systems employ mechanical or hard-coded deadband control behaviors that are unresponsive to changing energy costs and weather conditions. In this paper, we investigate the potential of electric baseboard heaters to maintain a comfortable temperature while optimizing electricity consumption given weather forecasts and price data. We first propose a distributed system architecture that utilizes mobile application platforms. We then develop, assemble, and deploy a sensor network and Internet server to collect real-time temperature data from an apartment. With these...

Velocity Predictors for Predictive Energy Management in Hybrid Electric Vehicles

Sun, Chao
Hu, Xiaosong
Moura, Scott J.
Sun, Fengchun
2015

The performance and practicality of predictive energy management in hybrid electric vehicles (HEVs) are highly dependent on the forecast of future vehicular velocities, both in terms of accuracy and computational efficiency. In this brief, we provide a comprehensive comparative analysis of three velocity prediction strategies, applied within a model predictive control framework. The prediction process is performed over each receding horizon, and the predicted velocities are utilized for fuel economy optimization of a power-split HEV. We assume that no telemetry or on-board sensor...

Dynamic Traffic Feedback Data Enabled Energy Management in Plug-in Hybrid Electric Vehicles

Sun, Chao
Moura, Scott Jason
Hu, Xiaosong
Hedrick, J. Karl
Sun, Fengchun
2015

Recent advances in traffic monitoring systems have made real-time traffic velocity data ubiquitously accessible for drivers. This paper develops a traffic data-enabled predictive energy management framework for a power-split plug-in hybrid electric vehicle (PHEV). Compared with conventional model predictive control (MPC), an additional supervisory state of charge (SoC) planning level is constructed based on real-time traffic data. A power balance-based PHEV model is developed for this upper level to rapidly generate battery SoC trajectories that are utilized as final-state constraints in...

Quantifying EV battery End-of-Life Through Analysis of Travel Needs with Vehicle Powertrain Models

Saxena, Samveg
Le Floch, Caroline
MacDonald, Jason
Moura, Scott
2015

Electric vehicles enable clean and efficient transportation, however concerns about range anxiety and battery degradation hinder EV adoption. The common definition for battery end-of-life is when 70–80% of original energy capacity remains, however little analysis is available to support this retirement threshold. By applying detailed physics-based models of EVs with data on how drivers use their cars, we show that EV batteries continue to meet daily travel needs of drivers well beyond capacity fade of 80% remaining energy storage capacity. Further, we show that EV batteries with...

Optimal Charging of Vehicle-to-Grid Fleets via PDE Aggregation Techniques

Le Floch, Caroline
Di Meglio, Florent
Moura, Scott
2015

This paper examines modeling and control of a large population of grid-connected plug-in electric vehicles (PEVs). PEV populations can be leveraged to provide valuable grid services when managed via model-based control. However, such grid services cannot sacrifice a PEV's primary purpose - mobility. We consider a centrally located fleet of identical PEVs that are distributed to and collected from drivers. The fleet also provides regulation services to the grid, contracted a priori. We develop a partial differential equation (PDE)- based technique for aggregating large populations of PEVs....

Sensitivity-Based Interval PDE Observer for Battery SOC Estimation

Perez, H. E.
Moura, S. J.
2015

Complex multi-partial differential equation (PDE) electrochemical battery models are characterized by parameters that are often difficult to measure or identify. This parametric uncertainty influences the state estimates of electrochemical model-based observers for applications such as state-of-charge (SOC) estimation. This paper develops a sensitivity-based interval observer that maps bounded parameter uncertainty to state estimation intervals, within the context of electrochemical PDE models and SOC estimation. Theoretically, this paper extends the notion of interval observers to PDE...

Integrating Traffic Velocity Data into Predictive Energy Management of Plug-in Hybrid Electric Vehicles

Sun, Chao
Sun, Fengchun
Hu, Xiaosong
Hedrick, J. Karl
Moura, Scott
2015

Recent advances in the traffic monitoring systems have made traffic velocity information accessible in real time. This paper proposes a supervised predictive energy management framework aiming to improve the fuel economy of a power-split plug-in hybrid electric vehicle (PHEV) by incorporating dynamic traffic feedback data. Compared with conventional model predictive control (MPC), an additional supervisory state of charge (SOC) planning level is constructed in this framework. A power balance PHEV model is developed for this upper level to rapidly generate optimal battery SOC trajectories,...

Data Enabled Predictive Energy Management of a PV-Battery Smart Home Nanogrid

Sun, Chao
Sun, Fengchun
Moura, Scott J.
2015

This paper proposes a data-enabled predictive energy management strategy for a smart home nanogrid (NG) that includes a photovoltaic system and second-life battery energy storage. The key novelty is utilizing data-based forecasts of future load demand, weather conditions, electricity price, and power plant CO2 emissions to improve the NG system efficiency. Specifically, a load demand forecast model is developed using an artificial neural network (ANN). The forecast model predicts load demand signals for a model predictive controller (MPC). Simulation results show that the data-enabled...

Modeling, Control, and Stability Analysis of Heterogeneous Thermostatically Controlled Load Populations Using Partial Differential Equations

Ghaffari, Azad
Moura, Scott
Krstic, Miroslav
2015

Thermostatically controlled loads (TCLs) account for more than one-third of the U.S. electricity consumption. Various techniques have been used to model TCL populations. A high-fidelity analytical model of heterogeneous TCL (HrTCL) populations is of special interest for both utility managers and customers (that facilitates the aggregate synthesis of power control in power networks). We present a deterministic hybrid partial differential equation (PDE) model which accounts for HrTCL populations and facilitates analysis of common scenarios like cold load pick up, cycling, and daily and/or...

Enhanced Performance of Li-Ion Batteries via Modified Reference Governors and Electrochemical Models

Perez, Hector
Shahmohammadhamedani, Niloofar
Moura, Scott
2015

This paper examines reference governor (RG) methods for satisfying state constraints in Li-ion batteries. Mathematically, these constraints are formulated from a first principles electrochemical model. Consequently, the constraints explicitly model specific degradation mechanisms, such as lithium plating, lithium depletion, and overheating. This contrasts with the present paradigm of limiting measured voltage, current, and/or temperature. The critical challenges, however, are that: 1) the electrochemical states evolve according to a system of nonlinear partial differential equations, and 2...