Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “battery control”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Modeling of RMS Current in CSI Filter Capacitor and Minimum Conduction Loss Operation of CSI-Fed PMSM Drives for Traction Applications

This paper presents a new minimum conduction loss (MCL) torque control algorithm for current source inverter- (CSI-) fed permanent-magnet synchronous machine drives that improves the overall machine drive efficiency by minimizing the combined conduction losses in the inverter and machine at each operating point. First, analytical models of conduction losses in CSI-fed motor drives are presented, and a closed-form expression for optimal d-axis stator current to achieve MCL operation is derived. An expression for the rms current in both wye- and delta-connected CSI output capacitors is derived. A detailed simulation model that emulates the operation of a 100 kW SiC CSI-fed integrated machine drive (IMD) has been developed based on experimental results and finite element analysis. This simulation model is used to evaluate the proposed MCL control algorithm applied to a CSI-fed IMD system for a battery-electric vehicle traction drive, and the predicted total drive system loss with MCL control is compared to predicted losses with maximum-torque-per-ampere (MTPA) and minimum dc-link current (MDCC) control. Results show that MCL control can achieve loss reductions compared to the other two control algorithms over a wide range of operating conditions, with significant loss reductions >20% in the medium-speed regime.

42 ENGINEERING↗
DOE OSTI2025

Do Mandates Deliver Cost Reductions for Energy Storage?

In 2013, California implemented a mandate directing the state’s investor-owned utilities to procure 1325 MW of energy storage, to help integrate nondispatchable renewable sources of energy and assist the state in meeting its environmental goals. This paper evaluates this policy’s impact of both battery deployment, and cost, finding that as of 2019, the state was effective in spurring nearly 500 MWh of battery storage deployment over what would have been installed in absence of the policy. This additive deployment would have the effect of reducing global battery cell costs by roughly $1.00/ kWh, based on learning by doing. To support these findings, we utilize both a difference in differences estimation, and a synthetic control analysis, both of which allow us to compare battery deployment in California, to deployment in other states. To pair deployment to cost reduction, we use a learning curve analysis, which links battery shipments to cell and storage block costs. For policymakers, these results provide evidence to the effectiveness of mandates in promoting storage deployment and help explain how these policies can induce downstream effects.

Boff, Daniel S.↗
DOE OSTI2022

Pumped Thermal Energy Storage With Liquid Storage

Pumped Thermal Energy Storage (PTES) uses electricity to power a heat pump; transferring heat from a cold space to a hot space forms a hot and a cold thermal reservoir, thereby storing energy. To discharge, the temperature difference between the two stores is used to drive a heat engine which generates electricity. In this chapter, PTES systems which store energy in liquids will be described. The chapter will concentrate on Joule-Brayton power cycles with molten salt storage. Part-load operation of Joule-Brayton PTES with liquid storage can be managed with "inventory control," and it is demonstrated that this control method leads to relatively good performance over a range of operating points.

Carnot batteries↗
DOE OSTI2023

On the Electrochemical Properties of Carbon-Coated NaCrO 2 for Na-Ion Batteries

NaCrO 2 is a promising cathode for Na-ion batteries. However, further studies of the mechanisms controlling its specific capacities and cycle stability are needed for real-world applications in the future. This study reveals, for the first time, that the typical specific capacity of ~110 mAh/g reported by many researchers when the charge/discharge voltage window is set between 2.0 and 3.6 V vs. Na/Na + is actually controlled by the low electronic conductivity at the electrode/electrolyte interface. Through wet solution mixing of NaCrO 2 particles with carbon precursors, uniform carbon coating can be formed on the surface of NaCrO 2 particles, leading to unprecedented specific capacities at 140 mAh/g, which is the highest specific capacity ever reported in the literature with the lower and upper cutoff voltages at the aforementioned values. However, such carbon-coated NaCrO 2 with ultrahigh specific capacity does not improve cycle stability because with the specific capacity at 140 mAh/g the Na deintercalation during charge is more than 50% Na ions per formula unit of NaCrO 2 which leads to irreversible redox reactions. The insights from this study provide a future direction to enhance the long-term cycle stability of NaCrO 2 through integrating carbon coating and doping.

25 ENERGY STORAGE↗
DOE OSTI2021

Multi-Time Scale Coordinated Control and Scheduling of Inverter-Based TCLs With Variable Wind Generation

To address microgrid tie flow errors caused by wind generation variability, here we propose and develop a multi-time scale coordinated control and scheduling strategy for inverter-based thermostatically controlled loads (TCLs). First, in hour-time scale, inverter-based TCLs with adjusting temperature set-point are modeled as virtual generators to compensate tie flow deviations in the day-ahead plan. Next, in minute-time scale, virtual batteries representing operating behaviors of inverter-based TCLs with frequency control are scheduled determined by the control of virtual generators in hour-time scale. The virtual batteries are scheduled to smooth out tie flow errors corresponding to day-ahead plan and hour-time scale schedules. The multi-time scale control methods are coordinated to employ the response potential of inverter-based TCLs and response curve-based methods are proposed to control inverter-based TCLs considering the customer privacy. The multi-time scale stochastic schedules which are based on response curves of inverter-based TCLs are coordinated to accommodate wind generation variability. Simulation results demonstrate that the microgrid tie flow errors are effectively mitigated by the proposed multi-time scale coordinated control and scheduling of inverter-based TCLs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Controlled lithium stripping enables a stable interface for long-cycling anode-free solid-state batteries

Anode-free solid-state batteries (AFSSBs) are a promising route toward achieving high energy density. In these cells, the anode contains no pre-stored lithium (Li). Instead, the entire Li inventory originates from the cathode and is freshly deposited onto a bare current collector during charging. However, achieving uniform and defect-free Li plating on this bare current collector remains a major challenge, often resulting in low Li plating/stripping efficiency and rapid capacity decay. Here, for the first time, operando neutron imaging is employed to visualize Li plating/stripping behavior in an anode-free full cell with LiNi0.82Mn0.07Co0.11O2 (NMC) as the cathode. Operando measurements reveal that complete stripping of Li leaves isolated Li residues on the current collector, which degrades the interfacial contact between the current collector and the solid-state electrolyte. To mitigate this interfacial issue and promote more uniform Li deposition, we implement a discharge-cutoff-voltage strategy that intentionally retains a thin residual Li layer after stripping. This preserved Li-containing interfacial reservoir not only improves interfacial contact but also serves as an in situ formed seed layer that enables more homogeneous subsequent Li plating. As a result, the optimized anode-free cell with limited stripping depth exhibits excellent long-term cycling stability, maintaining a discharge capacity of 112.1 mAh g−1 with a capacity retention of 80.6% and an average coulombic efficiency of approximately 99.9% after 500 cycles at 0.25 C. In contrast, the cell with a conventional discharge cutoff voltage of 2.8 V exhibits rapid capacity decay, retaining only 59.7 mAh g−1 after 50 cycles with a capacity retention of 40.7%. This work demonstrates that limiting deep stripping to preserve a thin Li-containing interfacial layer can effectively improve the cycling stability of sulfide-based AFSSBs.

Wang, Jiwei [Northeastern University, Boston]↗
DOE OSTI2022

Modelling and Experimental Validation of Improved Performance of Lithium-Ion Batteries Having Thick Electrodes with Laser-Ablated Micro-Structures

For widespread adoption of electric vehicles, lithium-ion batteries (LiBs) need to achieve energy densities of >275 Wh/kg, cost less than $100/Wh, and charge to more than 80% capacity within 15 minutes. Increasing the battery electrode thicknesses is one way to increase cell energy densities while also saving on cell manufacturing cost by increasing the ratio of electrode active material to inactive material within each cell. However, increased electrode loading is often accompanied by decreased Li+-ion diffusion across the full thick electrodes. This leads to significant cell polarization that prevents full capacity utilization and accelerates cell degradation, especially at fast charging/discharging rates. The introduction of secondary pore networks in thick battery electrodes alleviates some of the trade-offs between energy and power performance. These microstructures provide low tortuosity pathways for facile Li+-ion diffusion deep into the thick electrodes, diminishing detrimental concentration gradients within the cell. Ultrafast-pulsed laser ablation is a promising method to introduce micro pores or channels in thick battery electrodes as it allows for precise control of pattern geometries, results in minimal damage to the electrode and can be introduced into existing roll-to-roll electrode manufacturing lines. Herein, the limitations of thick planer electrodes and the advanced predictive models to identify optimal electrode patterns for improved cycling performance will be presented. The impact of electrode laser patterning to create secondary pore networks also will be discussed. Materials characterization techniques (SEM-EDS, XRD) were used to explore the affect ultrafast laser ablation had on the electrode materials’ morphology and structure. The improvements in the patterned electrodes’ electrochemical cycling performances and degrees of wetting will be compared to a pristine baseline case. Finally, the discrepancies between experimentally obtained data and model predictions will be explained.

DIRECT ENERGY CONVERSION,ENERGY STORAGE↗
DOE OSTI2021

Real-time Optimal Dispatch of Behind-the-Meter DERs for Secondary Frequency Regulation

Active distribution networks (ADNs) can provide grid services such as peak load shaving, loss reduction, VoltNar control, congestion management, and frequency regulation. The fast response of inverter-based distributed energy resources (DERs) and battery storage systems enables them to provide ramping support and frequency control. This paper proposes a real-time optimization approach for behind-the-meter DERs to participate in the secondary frequency regulation. The proposed approach determines optimal set-points of output power of DERs to respond to requests from system operators (SOs) in realtime to maintain the frequency of the system at the nominal value. To satisfy the real-time requirement for the secondary frequency control, the nonlinear AC power flow model is linearized considering power losses in the system to achieve both high computational speed and acceptable accuracy. The optimization problem is rerun in a closed loop manner until the mismatch between the requested power by the system operators and actual delivered power at the substation reaches an acceptable tolerance. Furthermore, the proposed approach is validated using modified versions of the IEEE 33-bus and IEEE 69-bus distribution systems. Although the contribution of a single distribution system in the frequency regulation may not be significant, stacked and coordinated contributions from several distribution systems can provide frequency regulation and other grid services at scale.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Scalable Predictive Control and Optimization for Grid Integration of Large-Scale Distributed Energy Resources: Preprint

Integration of a large number of distributed energy resources (DERs) into the power grid needs a scalable power balancing method. We formulate the power balancing problem as a look-ahead optimization problem to be solved sequentially by a power distribution system aggregator based on a model predictive control (MPC) framework. Solving large-scale look-ahead control problem requires proper configuration of the control steps. In this paper, to solve large-scale control problems, we propose a variable time granularity where control time steps nearby the current control step have finer resolutions. The aggregator objective includes maximization of power production revenue and minimization of power purchasing expense, renewable power curtailment, and mileage costs for energy storage and electric vehicle (EV) charging stations while satisfying system capacity and operational constraints. The control problem is formulated as a mixed-integer linear program (MILP) and solved using the XpressMP solver. We perform simulations considering a copper plate representation of a large distribution network consisting of 2507 devices (controllable DERs) including curtailable photovoltaics (PVs), energy storage batteries, EV charging stations, and buildings with heating, ventilation, and air conditioning units (HVACs). We show the effectiveness of the proposed approach in managing DERs interactively for maximum energy trading profit and local supply-demand power balancing. Finally, we demonstrate that the proposed method outperformed other benchmark controllers regarding computation time without compromising operational performance.

DER↗
DOE OSTI2022

Scalable Predictive Control and Optimization for Grid Integration of Large-Scale Distributed Energy Resources

Integrating a large number of distributed energy resources (DERs) into the power grid needs a scalable power balancing method. We formulate the power balancing problem as a look-ahead optimization problem to be solved sequentially by a power distribution system aggregator based on a model predictive control (MPC) framework. Solving large-scale look-ahead control problems requires proper configuration of the control steps. In this paper, to solve large-scale control problems, we propose a variable time granularity where control time steps nearby the current control step have finer resolutions. The aggregator objective includes maximization of power production revenue and minimization of power purchasing expense, renewable power curtailment, and mileage costs for energy storage and electric vehicle (EV) charging stations while satisfying system capacity and operational constraints. The control problem is formulated as a mixed-integer linear program (MILP) and solved using the XpressMP solver. We perform simulations considering a copper plate representation of a large distribution network consisting of 2507 devices (controllable DERs), including curtailable photovoltaics (PVs), energy storage batteries, EV charging stations, and buildings with heating, ventilation, and air conditioning units (HVACs). We show the effectiveness of the proposed approach in managing DERs interactively for maximum energy trading profit and local supply-demand power balancing. Finally, we demonstrate that the proposed method outperforms other benchmark controllers regarding computation time without compromising operational performance.

DER↗
DOE OSTI2020

Investigation of Active Life Balancing to Recondition Li-ion Battery Packs for 2nd Life

An investigation is presented into the application of active life balancing battery management systems to recondition inhomogeneous Li-ion battery packs and achieve homogeneity in capacity for second life. This paper proposes a life balancing objective map, which controls the state of charge references for each cell in a battery pack based on its capacity relative to other cells. The impacts of life balancing objective maps on the reconditioning time and overall pack capacity fade are considered. Moreover, the proposed approach accounts for various load and environmental effects, including depth-of-discharge, battery pack temperature, number of cycles per day, and cells’ resting time at various states of charge. The study results in a battery pack with convergent capacities achieved in minimal time, while curtailing overall capacity fade. Simulation results for a battery pack with sixteen series connected 75 Ah Kokam NMC cells with 3.6% initial capacity imbalance are presented, indicating a reconditioning time of 1.34 months with a final capacity imbalance of 0.1% and an overall capacity fade of 0.005%.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Design of a Multi-Chemistry Battery Pack System for Behind-the-Meter Storage Applications

Battery management systems (BMS) are essential for a battery pack's safe operation and longevity. This paper presents an active balancing method-based BMS for different cell chemistry structures to be used in behind-the-meter storage (BTMS) applications. The proposed system utilizes modular isolated dual active bridge (DAB) DC/DC converters to actively balance the battery pack through a low voltage (LV) bus. A supervisory controller monitors all the cell voltage, current, and state of charge (SOC) values. Based on the estimation of the SOCs, reference currents for the DAB converters are generated by the supervisory controller. Detailed modeling and the control approach of the modular DAB converters are presented in the paper. Moreover, the control strategy of the supervisory control is also analyzed. The proposed method and structure can be extended to any combination of the number of cells to design the battery pack. Simulation results are provided for a system consisting of three cells in parallel to form a cell block and three cell blocks in series to form the battery module. Experimental results are provided for three modular DAB converters operating with a LiFeMnPO4 prismatic cell with 3.2V, 20Ah rated values.

battery management systems↗
DOE OSTI2020

DFT modelling of explicit solid–solid interfaces in batteries: methods and challenges

Density Functional Theory (DFT) calculations of electrode material properties in high energy density storage devices like lithium batteries have been standard practice for decades. By contrast, DFT modelling of explicit interfaces in batteries arguably lacks universally adopted methodology and needs further conceptual development. In this paper, we focus on solid–solid interfaces, which are ubiquitous not just in all-solid state batteries; liquid-electrolyte-based batteries often rely on thin, solid passivating films on electrode surfaces to function. We use metal anode calculations to illustrate that explicit interface models are critical for elucidating contact potentials, electric fields at interfaces, and kinetic stability with respect to parasitic reactions. The examples emphasize three key challenges: (1) the “dirty” nature of most battery electrode surfaces; (2) voltage calibration and control; and (3) the fact that interfacial structures are governed by kinetics, not thermodynamics. To meet these challenges, developing new computational techniques and importing insights from other electrochemical disciplines will be beneficial.

25 ENERGY STORAGE↗
DOE OSTI2023

Growth of titania and tin oxide from Ti 2 SnC via rapid thermal oxidation in air for lithium-ion battery application

Herein, we report the synthesis of TiO 2 –SnO 2 –C/carbide hybrid electrode materials for Li-ion batteries (LIBs) via two different methods of controlled oxidation of layered Ti 2 SnC. The material was partially oxidized in an open-air furnace (OAF) or using a rapid thermal annealing (RTA) approach to obtain the desired TiO 2 –SnO 2 –C/carbide hybrid material; the carbide phase encompassed both residual Ti 2 SnC and TiC as a reaction product. We tested the oxidized materials as an anode in a half cell to investigate their electrochemical performance in LIBs. Analysis of the various oxidation conditions indicated the highest initial lithiation capacity of 838 mAh/g at 100 mA/g for the sample oxidized in the OAF at 700°C for 1 h. Still, the delithiation capacity dropped to 427 mAh/g and faded over cycling. Long-term cycling demonstrated that the RTA sample treated at 800°C for 30 s was the most efficient, as it demonstrated a reversible capacity of around 270 mAh/g after 150 cycles, as well as a specific capacity of about 150 mAh/g under high cycling rate (2000 mA/g). Given the materials’ promising performance, this processing method could likely be applied to many other members of the MAX family, with a wide range of energy storage applications.

25 ENERGY STORAGE↗
DOE OSTI2024

pnnl/EZBattery

Cell performance optimization is important for improving the system efficiency of a redox flow battery. To gain better insights into key controlling factors Of system efficiency, this work first proposed a theoretical model for a unit cell by extending a two-dimensional analytic model to a full cell. The model is then used for cell performance optimization after validating it with experimental and numerical modeling data.

Bao, Jie↗
DOE OSTI2021

Integration of a DER Management System in Riverside. Final report

The tasks in this project covered various aspects, including algorithm development, algorithm integration into a commercial Active Network Management (ANM) platform, hardware-in-the-loop (HIL) testing in an industry-standard testing platform, pilot demonstration in Riverside, California, and also cost and benefit analysis. The DERMS platform in this project can host different algorithms developed on different platforms (e.g., MATLAB and Python) and it can interact with different hardware devices (e.g., different PV inverters, battery inverters, and different sensors). The DER control solution are based on an advanced model-free, layered, and clustered DER control paradigm. At the core of the DER control algorithms was the concept of Extremum Seeking (ES), which is a model-free probing-based control technique. The ES-based control algorithms were tested on major real-world inverters; both individually and in a cluster. It was shown that even legacy equipment (or when paired with a few additional advanced equipment) can support such advanced control. The monitoring algorithms utilize a heterogeneous set of legacy and advanced sensor measurements, such as behind-the-meter DER sensors, distribution-level Phase Measurement Units, distribution-substation Supervisory Control and Data Acquisition (SCADA), and line current sensors, with their limited availability; in order to infer practical network conditions. Sensor data are utilized to achieve resource forecasting, phase identification, and distribution system state estimation. The technology that was developed and demonstrated in this project could be transformational to utilities, including the smaller municipal utilities such as in Riverside, which may not have the resources to deploy advanced distribution system and DERMS solutions in order to support high penetration of solar power integration. This project created a real-world prototype to provide utilities with an assessment of smart grid monitoring and control technologies.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

The Highly Integrated Vehicle Ecosystem (HIVE): A Platform for Managing the Operations of On-Demand Vehicle Fleets

This paper introduces the Highly Integrated Vehicle Ecosystem (HIVE), a transportation modeling tool developed by within the Center for Integrated Mobility Sciences (CIMS) group at the National Renewable Energy Laboratory (NREL). HIVE is an agent-based supply/demand model for Mobility on Demand (MoD) which mixes agent-based modeling and centralized dispatch for automated and human-driven fleets and ride hail passengers. Research questions using HIVE span multiple categories, including intelligent fleet planning (assessing fleet, battery, and infrastructure investment decisions), intelligent fleet control (charge management, vehicle dispatching) and strategic business model decision-making (depot-based full-time drivers versus gig-based drivers, human-driven versus automated). The components of the HIVE model are explained and then HIVE is demonstrated in a case study using demand data from the New York City Taxi & Limousine Commission data set.

33 ADVANCED PROPULSION SYSTEMS↗