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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.

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At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Supersymmetric gauged $ \mathrm{U}{(1)}_{L_{\mu }-{L}_{\tau }} $ model for electron and muon (g - 2) anomaly

Minimal gauged U 1 L μ - L τ models can provide for an additional source for the muon anomalous magnetic moment however it is difficult to accommodate the discrepancy in the electron magnetic moment in tandem. Owing to the relative sign between the discrepancies in these quantities, it seems unlikely that they arise from the same source. We show that a supersymmetric (SUSY) gauged U 1 L μ - L τ model can accommodate both the muon and electron anomalous magnetic moments in a very simple and intuitive scenario, without utilizing lepton flavor violation. The currently allowed parameter space in this kind of a scenario is constrained from the latest LHC and various low energy experimental data,e.g., recent COHERENT data, CCFR, Borexino, BaBaR, supernova etc. These constraints, in conjunction with the requirement to explain both lepton magnetic moments, lead to an upper bound on the first generation slepton mass, a lower bound on the second generation slepton mass and constricts the allowed range for the new gauge boson mass and coupling. The scheme can be probed at the ongoing COHERENT and Coherent CAPTAIN-Mills experiments and at future experiments, e.g., DUNE, BELLE-II etc.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

What are the Impacts on the HVAC System when it Provides Frequency Regulation? – A Comprehensive Case Study with a Multi-Zone Variable Air Volume (VAV) System

Heating, ventilation, and air-conditioning (HVAC) systems in commercial buildings have proven to be a great asset for providing secondary frequency regulation (FR) service to the power grid. However, how the provision of FR service affects the HVAC system Quality of Service (QOS) is still largely unknown. In particular, there exists a controversy regarding the energy efficiency impact. This paper investigates how a HVAC system performance and its associated controls are impacted during and after the FR service. For the assessment, we developed a dynamic Modelica-based medium office building model as a virtual testbed with the Air Handling Unit (AHU) fans providing the FR service. Different regulation capacities (demand levels) and standard test signals under various load profiles in the U.S. are considered. The results show that FR has little or no impact on the HVAC operation and occupant thermal comfort while the building is providing the service if an appropriate regulation capacity is pre-determined. However, if the regulation capacity is overestimated, the quality of the FR service provided by the HVAC system and the HVAC energy efficiency will be affected due to the equipment operating constraints. In addition, the AHU supply air temperature fluctuates, and the controller cannot maintain the desired setpoint as the FR magnitude is increased. After the FR service time, the system takes a certain period to return to normal operation. The recovery period extends with the increase in the FR magnitude. For this case study, there exists a control conflict between the FR control and the existing HVAC control (from ASHRAE Guideline 36-2018) during high load conditions, causing the fan speed to saturate. The fan power consumption could increase significantly; up to 77% increase compared to the baseline was observed. This case study demonstrates that the HVAC system controls need to be enhanced and adapted to minimize the interaction between the FR controller and the indoor environmental controls in order to preserve the HVAC system QOS while (during and after) providing satisfactory FR service.

Lu, Xing↗
DOE OSTI2024

Using Mobile Charging Drones to Mitigate Battery Disruptions of Electric Vehicles on Highways

Our research explores innovative solutions to address the challenge of battery disruptions in electric vehicles (EVs) on highways. We propose a centralized fleet ownership model where a company manages a fleet of Mobile Charging Drones (MCDs) guided by a k-VRP (Vehicle Routing Problem) framework. This model is designed to tackle a multi-objective optimization issue with three primary goals: reduction of the overall operating costs, decrease in the cumulative waiting time, and minimization of the combined operating costs and waiting times. This approach extends beyond the usual VRP constraints, encompassing specific limitations for both MCDs and disrupted EVs (DEVs). Additionally, our study delves into the concept of decentralized fleet ownership through the lens of crowdsourcing. Preliminary numerical analyses indicate that the capital cost of MCDs is a significant factor on the charging service, and the system performance is sensitive to DEV owner's value of time (VOT) when VOTs are relatively low.

battery disruption↗
DOE OSTI2020

Optimal economic operation of liquid petroleum products pipeline systems

The majority of overland transport needs for crude petroleum and refined petroleum products are met using pipelines. Numerous studies have developed optimization methods for design of these systems in order to minimize construction costs while meeting capacity requirements. Here, we formulate problems to optimize the operations of existing single liquid commodity pipeline systems subject to physical flow and pump engineering constraints. The objectives are to maximize the economic value created for users of the system and to minimize operating costs. We present a general computational method for this class of continuous, non-convex nonlinear programs, and examine the use of pump operating settings and flow allocations as decision variables. Furthermore, the approach is applied to compute optimal operating regimes and perform engineering economic sensitivity analyses for a case study of a crude oil pipeline developed using publicly available data.

02 PETROLEUM↗
DOE OSTI2021

Achieving high ethylene yield in non-oxidative ethane dehydrogenation

Steam cracking of ethane, a non-catalytic thermochemical process, remains the dominant means of ethylene production. The severe reaction conditions and energy expenditure involved in this process incentivize the search for alternative reaction pathways and reactor designs which maximize ethylene yield while minimizing cost and energy input. Herein, we report a comparison of catalytic and non-catalytic non-oxidative dehydrogenation of ethane. We achieve ethylene yields as high as 67 % with an open tube quartz reactor without the use of a catalyst at residence times ~4 s. The open tube reactor design promotes simplicity, low cost, and negligible coke formation. Pristine quartz tubes were most effective, since coke formation was detected when defects were introduced by scratching the surface of the quartz. Surprisingly, the addition of solids to the quartz tube, such as quartz sand, alumina powder, or even Pt-based intermetallic catalysts, led to lower ethylene yield. Pt alloy catalysts are effective at lower temperatures, such as at 575 °C, but conversion is limited due to thermodynamic constraints. When operated at industrially relevant temperatures, such as 700 °C and above, these catalysts were not stable in our tests, causing ethylene yield to drop below that of the open tube. Furthermore, these results suggest that future research on non-oxidative dehydrogenation should be directed at optimizing reactor designs to improve the conversion of ethane to ethylene, since this approach shows promise for decentralized production of ethylene from natural gas deposits.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Dynamic Charging Rendezvous and Motion Planning for a Multi-AGV Team Including a Mobile Charging Host

Teams of automated battery-powered electric vehicles have the potential to execute complex mission tasks in off-road environments for agriculture, military, and other applications. Limited onboard energy reserves hinder their adoption in large-scale resource-constrained environments, where recharging is a necessity. It may be infeasible to install a network of static charging stations in off-road environments. For this reason, dedicated mobile host vehicles with charging capabilities are proposed as a means to increase range and capabilities of the multivehicle team. Here, in this study, we consider an ad hoc planning framework, where results from a high-confidence trajectory planner are leveraged to plan charging rendezvous between a host and other worker vehicles in a receding horizon fashion to provide high confidence that energy reserves will not be prematurely exhausted. The core problem is posed so as to minimize the impact of recharging on the mission in terms of task delays, overall energy utilization, and costs of fast charging. Through extensive Monte Carlo simulations of an off-road mission, we show a decrease in task delays without substantial increases in energy needs by updating the charging rendezvous plan during the mission. However, if updates are made too often, model mismatch may cause unnecessary cycling and mission failure.

Energy constraints↗
DOE OSTI2024

Testing of a Line Driver With Configurable Pre-Emphasis on Lossy Transmission Lines

Rare-event physics experiments such as the Deep Underground Neutrino Experiment (DUNE) or the next Enriched Xenon Observatory (nEXO) experiment search for rare, low-energy events, detected by sensitive detectors immersed in a cryogenic noble liquid (e.g., liquid argon or xenon). Readout electronics used within such detectors must consume minimal power while operating reliably in cryogenic environments. Furthermore, in the case of nEXO, maximizing the radiopurity of the environment is vital to minimize background noise, thus placing strict limits on the volume of dielectric materials, leading to high-loss data cables spanning distances up to 12 m. Such cables cause high attenuation and intersymbol interference (ISI), resulting in a high bit-error rate (BER). These issues were addressed by developing an integrated line driver with configurable pre-emphasis in a 65-nm CMOS process. The pre-emphasis parameters can be programmed to minimize BER for specific cables and data rates under power constraints. Here, the driver was tested at both room and cryogenic temperatures. In both cases, the output BER was found to be strongly correlated with the pre-emphasis settings. Furthermore, analysis and simulation showed that adapting the pre-emphasis settings based on the incoming bit sequence can further improve performance with minimal changes to the current solution.

47 OTHER INSTRUMENTATION↗
NASA NTRS1995

High frequency flow-structural interaction in dense subsonic fluids

Prediction of the detailed dynamic behavior in rocket propellant feed systems and engines and other such high-energy fluid systems requires precise analysis to assure structural performance. Designs sometimes require placement of bluff bodies in a flow passage. Additionally, there are flexibilities in ducts, liners, and piping systems. A design handbook and interactive data base have been developed for assessing flow/structural interactions to be used as a tool in design and development, to evaluate applicable geometries before problems develop, or to eliminate or minimize problems with existing hardware. This is a compilation of analytical/empirical data and techniques to evaluate detailed dynamic characteristics of both the fluid and structures. These techniques have direct applicability to rocket engine internal flow passages, hot gas drive systems, and vehicle propellant feed systems. Organization of the handbook is by basic geometries for estimating Strouhal numbers, added mass effects, mode shapes for various end constraints, critical onset flow conditions, and possible structural response amplitudes. Emphasis is on dense fluids and high structural loading potential for fatigue at low subsonic flow speeds where high-frequency excitations are possible. Avoidance and corrective measure illustrations are presented together with analytical curve fits for predictions compiled from a comprehensive data base.

Liu, Baw-Lin↗
DOE OSTI2023

An SU(5) × U(1)' SUSY GUT with a “vector-like chiral” fourth family to fit all low energy data, including the muon g – 2

An additional generation of quarks and leptons and their SUSY counterparts, which are vector-like under the Standard Model gauge group but are chiral with respect to the new U(1) 3–4 gauge symmetry, are added to the Minimal Supersymmetric Standard Model (MSSM). We show that this model is a GUT and unifies the three SM gauge couplings and also the additional U(1) 3–4 coupling at a GUT scale of ≈ 5 × 10 16 GeV and explains the experimentally observed deviation of the muon g – 2. We also fit the quark flavor changing processes consistent with the latest experimental data and look at the effect of the new particles on the W boson mass without obviously conflicting with the observed masses of particles, CKM matrix elements, neutrino mixing angles, their mass differences, and the lepton-flavor violating bounds. This model predicts sparticle masses less than 25 TeV, with a gluino mass ≈ 2.3 – 3 TeV consistent with constraints, and one of the neutralinos as the LSP with a mass of ≈ 480 – 580 GeV, which is a potential dark matter candidate. The model is string theory motivated and predicts the VL quarks, leptons, a massive Z' and two Dirac neutrinos at the TeV scale and the branching ratios of μ → eγ, τ → μγ and τ → 3μ with BR(μ → eγ) within reach of future experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

A Two-Level Model Predictive Control-Based Approach for Building Energy Management including Photovoltaics, Energy Storage, Solar Forecasting and Building Loads

This paper uses a two-level model predictive control-based approach for the coordinated control and energy management of an integrated system that includes photovoltaic (PV) generation, energy storage, and building loads. Novel features of the proposed local controller include (1) the ability to simultaneously manage building loads and energy storage to achieve different operational objectives such as energy efficiency, economic cost efficiency, demand response and grid optimization through the design of specific power trajectory tracking performance functionals, (2) an energy trim function that minimizes the impact of solar forecasting errors on system performance, and (3) the design of a state of charge controller that uses day-ahead forecast of solar power and building loads to intialize energy storage at the start of each day. The local controller is tested in simulation using an exemplary system with PV generation, energy storage and dispatchable building loads. Two sample days with different PV forecasts and multiple case scenarios are considered, and the performance of the algorithm in managing the real and reactive net building load trajectories and the ramp rate of PV injections into the utility network are evaluated. The simulations are based on actual forecasted and measured PV data, and the results show that the local controller meets the tracking requirements for real and reactive power within the operating constraints of the building.

14 SOLAR ENERGY↗
DOE OSTI2022

Multi-Fidelity Stochastic Economic Dispatch for Operating Low Carbon Power Grids

Grid operators can address the inherently stochastic nature of renewables by solving a two-stage stochastic programming model that minimizes the cost of dispatch decisions while accounting for the complex grid dynamics. It is common to use a sample average approximation to estimate the expectation of the second stage costs in this model. However, the large sample count needed for numerical accuracy makes effective modeling large-scale electric grids computationally intractable. We introduce a control variate multi-fidelity estimator for the second-stage recourse that enables high quality dispatch decisions in real-time with a reduced computational burden. We obtain a hierarchy of model fidelities by linearizing the AC power flow system representation to DC power flow, and by relaxing transmission and voltage network constraints. We evaluate the performance of our proposed method on a synthetic grid with 73 buses against a deterministic baseline with persistence forecast and a high-fidelity reference. Our analysis shows a computational speed-up of 7.62x with a minimal loss in accuracy. The multi-fidelity method is well suited to fidelity combinations that use a simplified network topology in their lower fidelity model and is an attractive option for applications where accurate grid modeling needed on a limited computational budget.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Quantifying Quantum Chaos through Microcanonical Distributions of Entanglement

A characteristic feature of “quantum chaotic” systems is that their eigenspectra and eigenstates display universal statistical properties described by random matrix theory (RMT). However, eigenstates of local systems also encode structure beyond RMT. To capture this feature, we introduce a framework that allows us to compare the properties of eigenstates in local systems with those of pure random states. In particular, our framework defines a notion of distance between quantum state ensembles that utilizes the Kullback-Leibler divergence to compare the microcanonical distribution of entanglement entropy (EE) of eigenstates with a reference RMT distribution generated by pure random states (with appropriate constraints). This notion gives rise to a quantitative metric for quantum chaos that not only accounts for averages of the distributions but also higher moments. The differences in moments are compared on a highly resolved scale set by the standard deviation of the RMT distribution, which is exponentially small in system size. As a result, the metric can distinguish between chaotic and integrable behaviors and, in addition, quantify and compare the of chaos (in terms of proximity to RMT behavior) between two systems that are assumed to be chaotic. We implement our framework in local, minimally structured, Floquet random circuits, as well as a canonical family of many-body Hamiltonians, the mixed-field Ising model (MFIM). Importantly, for Hamiltonian systems, we find that the reference random distribution must be appropriately constrained to incorporate the effect of energy conservation in order to describe the ensemble properties of midspectrum eigenstates. The metric captures deviations from RMT across all models and parameters, including those that have been previously identified as strongly chaotic, and for which other diagnostics of chaos such as level spacing statistics look strongly thermal. In Floquet circuits, the dominant source of deviations is the second moment of the distribution, and this persists for all system sizes. For the MFIM, we find significant variation of the KL divergence in parameter space. Notably, we find a small region where deviations from RMT are minimized, suggesting that “maximally chaotic” Hamiltonians may exist in fine-tuned pockets of parameter space. Published by the American Physical Society 2024

Physics↗
NASA NTRS2019

Program Management for Concurrent University Satellite Programs, Including Propellant Feed System Design Elements

Propulsion options for CubeSats are limited but are necessary for the CubeSat industry to continue future growth. Challenges to CubeSat propulsion include volume/mass constraints, availability of sufficiently small and certified hardware, secondary payload status, safe storage of high energy, and power requirements. A multi-mode (chemical and electric) thruster was developed by at the Missouri University of Science and Technology (Missouri S&T) to enable CubeSat propulsion missions. Two satellite buses, a 3U and 6U, are being developed by the M-SAT satellite research team at Missouri S&T to demonstrate the multi-mode thruster's capabilities. Two key challenges related to these missions are the development of the feed system to support the thruster and management of the two programs' personnel, resources, timelines, and budgets. The feed system was designed to support the unique needs of the thruster including material compatibility with the custom ionic liquid, variable flow rate, high pressurization, and high voltage within the constraints and budget of a student-designed propulsion system. The feed system was also designed to minimize risk as a secondary payload. This resulted in the development of a unique method to pressurize propellant stored in the feed system tubing. Within the expected operating pressure range, the method was experimentally shown to provide sufficient pressure and propellant volume to the thruster to meet mission success criteria. The 3U and 6U CubeSat buses were designed concurrently with complimentary payloads, hardware, objectives, and team structures. Resources such as personnel, lab space, and time had to be carefully balanced between the two teams. With proper management, the two programs have been able to support one another, providing valuable insight and collaboration between the two teams. Lessons learned include experience with design, testing, and assembly of hardware, team training/mentoring and motivation, improved documentation practices, and risk management.

Withrow, Shannah Nichole↗
DOE OSTI2024

Experimental Safe Extremum Seeking for Accelerators

Here, we demonstrate the recent designs of safe extremum seeking (Safe ES) on the 1-km-long charged particle accelerator at the Los Alamos Neutron Science Center (LANSCE). Safe ES is a modification of extremum seeking (ES) which, in addition to minimizing an analytically unknown cost, also employs a safety filter based on an analytically unknown control barrier function (CBF) safety metric. Tuning is necessitated by accelerators being large complex systems, with many drifting parameters due to thermal effects and degradation. At the same time, safe operation (the maintenance of state constraints) is crucial, as damage brings astronomical costs, both financially and in operation downtime. Our measured (but analytically unknown) safety metric is the beam current. We perform multivariable Safe ES on three accelerator applications, in which we adapt 4, 6, and 3 magnet strength parameters, respectively. Two of the three applications are for validated simulation models of beamlines at LANSCE: the first for the proton radiography (pRad) beamline of 800-MeV protons for spot size tuning; the second on a high-performance code, HPSim, for tuning the low-energy beam transport (LEBT) region that contains a beam of 750-keV protons. The third is an experimental tuning of the steering magnets in the LEBT at LANSCE.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Distributed Optimal Power Management for Battery Energy Storage Systems: A Novel Accelerated Tracking ADMM Approach

Optimal power management (OPM) is critical for large-scale battery energy storage systems. Today’s methods often require formidable computational effort due to the design based on centralized numerical optimization. Thus, this paper investigates computationally distributed OPM where the agents based on the cells communicate over a network to cooperatively solve the OPM problem. We propose an accelerated tracking alternating direction method of multipliers (ADMM) algorithm to solve the distributed OPM. The proposed algorithm embeds dynamic average consensus and Nesterov’s acceleration technique in the ADMM algorithm. Not only is the proposed algorithm fully distributed without a need for fusion or aggregating nodes, but it also accelerates convergence. The paper formulates the OPM in a model predictive control framework where it seeks to regulate the charging/discharging power of each battery cell to minimize the total power losses and promote balanced use of the constituent cells while complying with the safety constraints. The paper provides ample simulation results to demonstrate the effectiveness and advantages of the proposed distributed OPM in terms of computation and convergence.

Farakhor, Amir↗
NASA NTRS2016

Virtual Flight Demonstration of the Stratospheric Dual-Aircraft Platform

A baseline configuration for the dual-aircraft platform (DAP) concept is described and evaluated in a physics-based flight dynamics simulations for two month-long missions as a communications relay in the lower stratosphere above central Florida, within 150-miles of downtown Orlando.The DAP configuration features two large glider-like (130 ft wing span) unmanned aerial vehicles connected via a long adjustable cable (total extendible length of 3000 ft) which effectively sail without propulsion using available wind shear. Use of onboard LiDAR wind profilers to forecast wind distributions are found to be necessary to enable the platform to efficiently adjust flight conditions to remain sailing by finding sufficient wind shear across the platform. The aircraft derive power from solar cells, like a conventional solar aircraft, but also extract wind power using the propeller as a turbine when there is an excess of wind shear available.Month-long atmospheric profiles (at 3-5 min intervals) in the vicinity of 60,000-ft are derived from archived data measured by the 50-Mhz Doppler Radar Wind Profiler at Cape Canaveral and used in the DAP flight simulations. A cursory evaluation of these datasets show that sufficient wind shear for DAP sailing is persistent, suggesting that DAP could potentially sail over 90% of the month-long durations even when limited by modest ascent/descent rates.DAP's novel guidance software uses a non-linear constrained optimization technique to define waypoints such that sailing mode of flight is maintained where possible, and minimal thrust is required where sailing is not practical. A set of constraints are identified which result in waypoints that enable efficient flight (i.e., minimal use of propulsion) over the two month-long flight simulations. Waypoint solutions may need to be tabulated for a wide range of potential atmospheric conditions and stored onboard for quick retrieval on a real DAP.DAP's flight control software uses an unconventional mixture of spacecraft and aircraft control techniques. Flight simulations confirms that this controls approach enables the platform to consistently reach successive waypoints over the month-long flight simulations.The ability of DAP to transition between the sailing mode (i.e., cable tension is high) and standard formation flight (i.e., cable tension is low) is a vital capability (e.g., to enable intermittent turns while stationkeeping). A new method to perform these transitions has been identified and characterized with flight simulation which requires special aircraft modifications.The energy-usage of the DAP configuration during two month-long stationkeeping missions over central Florida (i.e., stationkeeping over Orlando) is evaluated and compared to that of a pure solar aircraft of the same weight and aerodynamic performance. DAP is shown to consistently reduce net propulsion usage while simultaneously increasing solar energy capture.A baseline 700 GHz communications system is described and its performance evaluated for the proposed mission over central Florida. It is found that the variable roll orientation of the aircraft would increase the power required to maintain coverage over the stationkeeping radius of 150 miles (e.g., by as much as 100% when DAP is 150 miles from Orlando), compared to level flight. This effect can be mitigated via additional antenna design complexity or a more restricted stationkeeping radius.

Demonstrations↗
DOE OSTI2022

Dark Energy Survey year 3 results: Constraints on cosmological parameters and galaxy-bias models from galaxy clustering and galaxy-galaxy lensing using the redMaGiC sample

We constrain cosmological parameters and galaxy-bias parameters using the combination of galaxy clustering and galaxy-galaxy lensing measurements from the Dark Energy Survey (DES) year-3 data. We describe our modeling framework and choice of scales analyzed, validating their robustness to theoretical uncertainties in small-scale clustering by analyzing simulated data. Using a linear galaxy-bias model and redMaGiC galaxy sample, we obtain 10% constraints on the matter density of the Universe. Here, we also implement a nonlinear galaxy-bias model to probe smaller scales that includes parametrization based on hybrid perturbation theory and find that it leads to a 17% gain in cosmological constraining power. We perform robustness tests of our methodology pipeline and demonstrate stability of the constraints to changes in the theory model. Using the redMaGiC galaxy sample as foreground lens galaxies and adopting the best-fitting cosmological parameters from DES year-1 data, we find the galaxy clustering and galaxy-galaxy lensing measurements to exhibit significant signals akin to decorrelation between galaxies and mass on large scales, which is not expected in any current models. This likely systematic measurement error biases our constraints on galaxy bias and the S 8 parameter. We find that a scale-, redshift- and sky-area-independent phenomenological decorrelation parameter can effectively capture this inconsistency between the galaxy clustering and galaxy-galaxy lensing. We trace the source of this correlation to a color-dependent photometric issue and minimize its impact on our result by changing the selection criteria of redMaGiC galaxies. Using this new sample, our constraints on the S 8 parameter are consistent with previous studies and we find a small shift in the Ω m constraints compared to the fiducial redMaGiC sample. We infer the constraints on the mean host-halo mass of the redMaGiC galaxies in this new sample from the large-scale bias constraints, finding the galaxies occupy halos of mass approximately 1.6 × 10 13 M ⊙ /h.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Integrating vehicle trajectory planning and arterial traffic management to facilitate eco-approach and departure deployment

Eco-approach and departure (EAD) enable continuous vehicle motion in urban signalized corridors. Since such a motion can extend to the EAD vehicles’ followers, it makes EAD a promising technology to benefit the traffic flow where automated vehicles and conventional vehicles coexist. Most existing EAD studies envision an ideal setting that neglects real-world operational conditions such as lane changes, multi-movement intersection configuration, partially automated fleet, and/or limited traffic state awareness. This study aims to fill the gap by designing an EAD algorithm considering real-world traffic operation constraints. The proposed algorithm uses a model predictive controller to minimize vehicle speed reduction and variation based on the real-time traffic signal control plan and measured queues at the intersection. The required inputs are readily available at many modern intersections. We observed that the proposed controller’s performance might degrade because of lane-changing maneuvers and lead-left turn traffic signals. These observations motivated our development of a lane change management strategy and a signal control implementation strategy to facilitate the EAD implementation. The lane change management strategies separate the EAD operations and lane-changing maneuvers in time and space. The signal control implementation strategy applies lag-left turn signals to enable EAD operation for both the through and left-turn vehicles. Compared to the non-EAD case, our EAD approach produces 2.5% to 7.8% energy savings while keeping similar intersection mobility. Notably, this approach brings about 2.5% to 3.6% energy savings in a 2% CAV case. This result demonstrates the feasibility of deploying EAD at low connected automated vehicle penetration rates.

Arterial corridor management↗