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

Sun, Chao
Scott Moura
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...

Analytic Modeling and Integral Control of Heterogeneous Thermostatically Controlled Load Populations

Ghaffari, Azad
Scott Moura
Krstic, Miroslav
2014

Thermostatically controlled loads (TCLs) account for approximately 50% of U.S. electricity consumption. Various techniques have been developed to model TCL populations. A High-fidelity analytical model of heterogeneous TCL populations facilitates the aggregate synthesis of power control in power networks. Such a model assists the utility manager to increase the stability margin of the network. The model, also, assists the customer to schedule his/her tasks in order to reduce his/her energy cost. We present a deterministic hybrid partial differential equation (PDE) model which accounts for...

Velocity Predictors for Predictive Energy Management in Hybrid Electric Vehicles

Sun, Chao
Hu, Xiaosong
Scott Moura
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...

Model Predictive Control of Residential Baseboard Heaters with Distributed System Architecture

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

Fast Charging Batteries via Electrochemical Model-based Control

Scott Moura
2014

Title: Fast Charging Batteries via ElectroChemical Model-Based Control In telecommunications, there were 5.2B active mobile handsets and over 1.7B mobile phone sales worldwide for 2012. Mobile phones are also a powerful tool for solving poverty and financial inequity in third world countries. In electrified transportation, there were 53,000 were plug-in electric vehicles sold in the U.S. for 2012. Despite growing sales, range anxiety is considered the largest inhibitor of electrified transportation. Significant reduction in charge times, e.g. comparable to filling a gas tank, would...

Comparison of Velocity Forecasting Strategies for Predictive Control in HEVs

Sun, Chao
Hu, Xiaosong
Scott Moura
Sun, Fengchun
2014

The performance of model predictive control (MPC) for energy management in hybrid electric vehicles (HEVS) is strongly dependent on the projected future driving profile. This paper proposes a novel velocity forecasting method based on artificial neural networks (ANN). The objective is to improve the fuel economy of a power-split HEV in a nonlinear MPC framework. In this study, no telemetry or on-board sensor information is required. A comparative study is conducted between the ANN-based method and two other velocity predictors: generalized exponentially varying and Markov-chain models. The...

Sensitivity-Based Interval PDE Observer for Battery SOC Estimation

Perez, H. E.
Scott Moura
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...

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

Sun, Chao
Sun, Fengchun
Scott Moura
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...

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

Perez, Hector
Shahmohammadhamedani, Niloofar
Scott Moura
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...

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

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