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At least 73 records · Page 4

Intercomparison of Aerosol Instrumental Responses Using AEROTRAK, SMPS, and APS in a Simulated Building

In this work, three aerosol instruments were intercompared by using data collected from field campaigns in a simulated building environment during the last quarter of 2020 from October to December at Oak Ridge National Laboratory. The three aerosol instruments—AeroTrak Model 9110, Scanning Mobility Particle Spectrometer (SMPS) 3080L + 3025A, and Aerodynamic Particle Sizer (APS) 3320—were manufactured by TSI Inc. to perform in situ measurements of particle number concentration in the air. These instruments were co-located in one room in which an aerosol generator was used to produce a defined aerosol population for the instruments to sample and detect in each campaign. The SMPS measured aerosol particles with diameters from 0.01 to 0.7 µm, APS measured aerosol particles with diameters from 0.5 to 20 µm, and AeroTrak measured aerosol particles with diameters from 0.1 to 10 µm. The results suggest that although AeroTrak is fast and easy to use, it does not provide measurements comparable with those obtained by SMPS and APS. The differences in particle counts were orders of magnitude in size (i.e., the AeroTrak data were unreasonably small in the tested scenarios). The results clearly indicate that AeroTrak should not be used in ambient applications in which the level of particle concentration is expected to be high. This would cause difficulty to a campaign in which the dilution factor is unknow a priori. The high particle concentration could also lead to an erroneous aerosol size distribution (e.g., a bimodal size distribution was measured as opposed to a single-mode one). The number concentration limit that AeroTrak is expected to run reliably (i.e., with a counting coincidence error less than ±10%) is approximately three to four per cubic centimeter. This suggests that the instrument is best used in a clean room environment, not in an ambient or indoor application, such as the Flexible Research Platform campaigns.

47 OTHER INSTRUMENTATION↗

A semi-coupled aero-servo-hydro numerical model for floating vertical axis wind turbines operating on TLPs

Floating vertical axis wind turbines (VAWTs) have many advantages over floating horizontal axis wind turbines (HAWTs) at large scales in deep water; however, there are several key challenges to overcome as well. One of the challenges is accurate prediction of the dynamic motion and loads performance of a floating VAWT. Here, a new semi-coupled aero-servo-hydro method is developed to assess dynamic responses of a floating VAWT by modeling the system as a 7-degree-of-freedom (7-DOF) model: the supporting platform is considered as a 6-DOF rigid body; the rotation of the rotor is considered as the 7th DOF. Aerodynamic, hydrodynamic, and mooring loads and control of the rotor speed are fully considered. This model can predict performance of floating VAWTs with reasonable fidelity according to validation with OrcaFlex through static and dynamic responses of a floating VAWT with Darrieus rotor operating on a new tension-leg platform (TLP). Being a reduced complexity model, the 7-DOF model can be efficiently applied to assess performance of the newly designed floating VAWT. This model is used to examine the relative contributions of aerodynamic and wave loads imparted to the floating system and the benefits of a three-bladed VAWT over a two-bladed VAWT through dynamic and fatigue analysis.

17 WIND ENERGY↗

Intracycle RPM control for vertical axis wind turbines

The wind energy market is currently dominated by horizontal axis wind turbines (HAWTs); however, vertical axis wind turbines (VAWTs) are emerging as a design alternative, especially for deep-water offshore siting due to their low center of gravity, ease of access to drivetrain components, and overall simplicity. Due to the absence of a pitch mechanism in large-scale Darrieus VAWTs, stall control has often been used to manage power and loads. Introducing a pitching mechanism in H-type VAWTs has been studied, but this diminishes the mechanical simplicity advantage, and the use of a pitching mechanism in a large-scale Darrieus-type VAWT is not practical. This work examines an innovative, alternative method to control the rotor dynamics of a large-scale 5 MW VAWT to maximize power while constraining loads without introducing any new or complex mechanical elements. This control strategy is termed intracycle revolution per minute (RPM) control, where the rotational speed of the turbine is allowed to vary in an optimal fashion with the azimuthal location of blades as opposed to typical constant RPM operation. An optimization framework is formulated for an open-loop optimal control problem and solved to maximize power subject to constraints on aerodynamic design loads. Results are presented to demonstrate the benefits and the performance limits of intracycle RPM control for large-scale 5 MW Darrieus VAWTs, namely, (1) power production (quantified in terms of AEP) that can be increased subject to baseline load limits and (2) opportunities to significantly increase AEP or decrease loads via intracycle RPM control that are examined for both two-bladed and three-bladed VAWTs.

17 WIND ENERGY↗

Multipoint Aerostructural Optimization of Wind Turbine Rotors Using a Coupled Blade‐Resolved Aerostructural Solver

Physics‐based design optimization workflows thread the needle between computational cost limitations and simulation complexity, often compromising between modeling detail and the range of operating design conditions. Multipoint aerostructural optimization of wind turbine rotors has so far been confined to low‐fidelity analyses or to high‐fidelity studies with simplified structural models, leaving the most complex design trade‐offs unexplored. We close this gap by performing the first tightly coupled gradient‐based multipoint aerostructural rotor optimization using 3D aerodynamic and structural solvers with discrete coupled adjoints. The optimizer simultaneously varies blade planform, airfoil shapes, and structural thickness through more than 270 design variables, minimizing a weighted combination of rotor mass and power across multiple wind speeds. Applied to a modified DTU 10‐MW benchmark under conservative structural and aerodynamic constraints, our multipoint optimization reduces rotor mass by up to 36% and increases power by 12%–15% across the main operating conditions; biasing the objective toward power yields power gains up to 18% and a 17% mass reduction. For a nominal wind distribution, 3‐point rotor designs accounting for low RPM and high thrust conditions capture dominant trade‐offs and outperform single‐point designs. Adding two off‐design points changes individual‐condition power by less than 3% but leaves the weighted average within 0.5%, and the mass‐power bias has a stronger effect on the final design than the operating‐point weighting itself. Our framework extends naturally to richer load cases and site‐specific wind distributions, providing a basis for high‐fidelity multipoint design earlier in industrial workflows.

17 WIND ENERGY↗

Coordinated Wind Power Plant and Battery Control for Active Power Services

This article considers joint active power control of wind turbines and battery storage to follow a plant-level power reference signal. The joint control dynamically curtails the energy from a subset of the wind turbines and stores or withdraws energy from the battery to meet the power reference setpoint while accounting for wind plant aerodynamic interactions, such as wake losses. As a use case, we study the performance of the controller in maintaining a constant power output over hourly periods. A wind plant operating in this way would rely much less on other grid resources to meet its contractual agreements, thereby improving grid reliability, especially in grids with high penetration of wind and solar generation. We compare the operation of the wind plant under joint active power control to standard power-maximizing control with battery support. We present an analysis of the performance of the control system architecture. To study the impact of the battery size on performance, we simulate a 50-MW wind plant supported by batteries ranging from 8 to 64?MWh. We then evaluate the over and undergeneration penalties incurred by the plant during the simulation period.

17 WIND ENERGY↗

Chapter 38: Aerodynamics of Wake Steering

This chapter discusses the mechanisms that enable wake steering within a wind farm with a focus on wake steering performed using yaw misaligned turbines as this is the most popular approach to wake steering, although there are others. Wake steering is a type of wind farm control in which wind turbines in a wind farm operate with an intentional yaw misalignment to mitigate the effects of its wake on downstream turbines in order to increase overall combined wind farm energy production. This chapter goes into detail regarding the dominant aerodynamic characteristics that are present when a turbine operates in yaw misaligned conditions and suggests analytical models that can capture these effects. A detailed analysis of large-scale flow structures generated in wind farm control through yaw misalignment is presented. A collection of counter-rotating vortices, produced from a misaligned turbine, deforms the shape of the wake and produces asymmetric effects with oppositely signed yaw angles. These vortices generated by an upstream misaligned turbine can also deflect wakes of downstream non-misaligned turbines. This chapter also addresses the importance of modeling these counter-rotating vortices in analytical models for wind farm control design and for accurately quantifying the impacts of wake steering on gains in power production in larger wind farms.

modeling↗

Aerodynamic and production comparison of wind farms with downwind versus conventional upwind turbines

Ever-increasing turbine scales and their associated logistical challenges have reignited questions about the performance of downwind rotor configurations. A particular potential benefit of downwind rotor configurations is the farm-scale power increase that may be conferred by tilt-driven downward wake entrainment and associated wake recovery. In this work, a comprehensive aerodynamic analysis is carried out to understand the mechanisms for wake entrainment and recovery across a spectrum of velocity and inflow alignment conditions on a small, structured farm in order to understand the impact of downwind rotors on farm production. The results show that the benefits demonstrated previously in the literature for downwind-rotor farms in aligned flows are fragile, and, outside of strong farm/flow alignment conditions, power production benefits for small farms with downwind rotor configurations are significantly if not completely mitigated by misalignment effects. The work indicates that farm-scale benefits for downwind rotors must be realized either from large-scale entrainment benefits, with more exotic farm arrangements that can take advantage of the aerodynamic effects, or from beneficial fatigue impacts from entrainment of less turbulent outer boundary layer flows.

17 WIND ENERGY↗

Going beyond BEM with BEM: an insight into dynamic inflow effects on floating wind turbines

Blade element momentum (BEM) theory is the backbone of many industry-standard wind turbine aerodynamic models. To be applied to a broader set of engineering problems, BEM models have been extended since their inception and now include several empirical corrections. These models have benefitted from decades of development and refinement and have been extensively used and validated, proving their adequacy in predicting aerodynamic forces of horizontal-axis wind turbine rotors in most scenarios. However, the analysis of floating offshore wind turbines (FOWTs) introduces new sets of challenges, especially if new-generation large and flexible machines are considered. In fact, due to the combined action of wind and waves and their interaction with the turbine structure and control system, these machines are subject to unsteady motion and thus unsteady inflow on the wind turbine's blades, which could put BEM models to the test. Consensus has not been reached on the accuracy limits of BEM in these conditions. This study contributes to the ongoing research on the topic by systematically comparing four different aerodynamic models, ranging from BEM to computational fluid dynamics, in an attempt to shed light on the unsteady aerodynamic phenomena that are at stake in FOWTs and whether BEM is able to model them appropriately. Simulations are performed on the UNAFLOW 1:75 scale rotor during imposed harmonic surge and pitch motion. Experimental results are available for these conditions and are used for baseline validation. The rotor is analyzed in both rated operating conditions and low wind speeds, where unsteady aerodynamic effects are expected to be more pronounced. Results show that BEM, despite its simplicity, can adequately model the aerodynamics of FOWTs in most conditions if augmented with a dynamic inflow model.

17 WIND ENERGY↗

Aerodynamic Rotor Design for a 25 MW Offshore Downwind Turbine

Continuously increasing offshore wind turbine scales require rotor designs that maximize power and performance. Downwind rotors offer advantages in lower mass due to reduced potential for tower strike, and is especially true at large scales, e.g., for a 25 MW turbine. In this study, three 25 MW downwind rotors, each with different prescribed lift coefficient distributions were designed (chord, geometry, and twist) and compared to maximize power production at unprecedented scales and Reynolds numbers, including a new approach to optimize rotor tilt and coning based on aeroelastic effects. To achieve this objective the design process was focused on achieving high power coefficients, while maximizing swept area and minimizing blade mass. Maximizing swept area was achieved by prescribing pre-cone and shaft tilt angles to ensure the aeroelastic orientation when the blades point upwards was nearly vertical at nearly rated conditions. Maximizing the power coefficient was achieved by prescribing axial induction factor and lift coefficient distributions which were then used as inputs for an inverse rotor design tool. The resulting rotors were then simulated to compare performance and subsequently optimized for minimum rotor mass. To achieve these goals, a high Reynolds number design space was developed using computational predictions as well as new empirical correlations for flatback airfoil drag and maximum lift. Within this design space, three rotors of small, medium and large chords were considered for clean airfoil conditions (effects of premature transition were also considered but did not significantly modify the design space). The results indicated that the medium chord design provided the best performance, producing the highest power in Region 2 from simulations while resulting in the lowest rotor mass, both of which support minimum LCOE. The methodology developed herein can be used for the design of other extreme-scale (upwind and downwind) turbines.

downwind rotors↗

Wind turbine performance enhancement with minimal structural load penalty: A design philosophy

The performance benefits of using tip devices on wind turbines has been well-documented. However, previous studies show that adding blade tip devices such as winglets leads to a significant increase in blade root bending moment, potentially requiring structural reinforcement with cost and weight drawbacks. A new and unique design philosophy for retrofit blade tip devices for wind turbines is presented. By balancing generated aerodynamic and centrifugal loads, these devices offer an increase in power production without the need for structural reinforcement. Predicted performance and cost benefits of using retrofit blade tip devices on the National Renewable Energy Laboratory 5 MW reference wind turbine are shown. Finally, the addition of blade tip devices resulted in significant improvements in the coefficient of power (C p ) and annual energy production (AEP).

17 WIND ENERGY↗

Wind turbine blade design with airfoil shape control using invertible neural networks

Wind turbine blade design is a highly multidisciplinary process that involves aerodynamics, structures, controls, manufacturing, costs, and other considerations. More efficient blade designs can be found by controlling the airfoil cross-sectional shapes simultaneously with the bulk blade twist and chord distributions. Prior work has focused on incorporating panel-based aerodynamic solvers with a blade design framework to allow for airfoil shape control within the design loop in a tractable manner. Including higher fidelity aerodynamic solvers, such as computational fluid dynamics, makes the design problem computationally intractable. In this work, we couple an invertible neural network trained on high-fidelity airfoil aerodynamic data to a turbine design framework to enable the design of airfoil cross sections within a larger blade design problem. We detail the methodology of this coupled framework and showcase its efficacy by aerostructurally redesigning the IEA 15-MW reference wind turbine blade. The coupled approach reduces the cost of energy by 0.9% compared to a more conventional design approach. This work enables the inclusion of high-fidelity aerodynamic data earlier in the design process, reducing cycle time and increasing certainty in the performance of the optimal design.

17 WIND ENERGY↗

Encoding nonlinear and unsteady aerodynamics of limit cycle oscillations using nonlinear sparse Bayesian learning

This article investigates the applicability of a recently proposed, nonlinear sparse Bayesian learning (NSBL) algorithm to identify and estimate the complex aerodynamics of limit cycle oscillations. NSBL provides a semi-analytical framework for determining the data-optimal sparse model nested within a (potentially) over-parameterized model. This is particularly relevant to nonlinear dynamical systems where modelling approaches involve the use of physics-based and data-driven components. In such cases, the data-driven components, where analytical descriptions of the physical processes are not readily available, are often prone to overfitting, meaning that the empirical aspects of these models will often involve the calibration of an unnecessarily large number of parameters. While an overparameterized model may fit the observed data well, such models may be inadequate for making predictions in regimes that are different from those wherein the data were recorded. In view of this, it is desirable to not only calibrate the model parameters, but also identify the optimal compromise between data fit and model complexity. In this article, we exhibit the optimal model discovery for an aeroelastic system wherein the structural dynamics are well-known and described by a differential equation model, coupled with a semi-empirical aerodynamic model for laminar separation flutter, resulting in low-amplitude limit cycle oscillations (LCO). To illustrate the performance of the algorithm, in this article, we use synthetic data and demonstrate the ability of the algorithm to correctly rediscover the optimal model and model parameters, given a known data-generating model. The synthetic data are generated from a forward simulation of a known differential equation model with parameters selected so as to mimic the dynamics observed in wind-tunnel experiments. Subsequently, we demonstrate the performance of the algorithm for model selection using noisy LCO data from wind tunnel experiments. As there is no ground truth available for the experimental data case, we provide a comparison between NSBL and Bayesian model selection to validate the results, and demonstrate the use of NSBL as an efficient alternative to traditional methods.

97 MATHEMATICS AND COMPUTING↗

Spatio-temporal and weather characterization of road loads of electrified heavy-duty commercial vehicles across U.S. interstate roads

Adoption of battery electric vehicles (BEV) in heavy duty (HD) commercial freight transportation is difficult due to technological and economic hurdles. Beyond safety and compliance, fleet and operational logistics necessitate both high uptime and parity with diesel system productivity/Total Cost of Ownership to support widespread deployment of electric powertrains. However, relatively high energy storage costs, along with the higher weight of BEV systems, limit the viability of HD commercial freight transport to shorter-range applications where smaller batteries will serve for mission energy requirements (single operational shift). Knowing the energy consumption and operating variations of these commercial vehicle systems is crucial for effectively sizing the energy storage systems. This paper is the first in a series of studies to understand the regional specific operating design domain variations of commercial Class 8 HD trucks and the associated impact to their energy requirements. In particular, the local weather conditions are shown to influence the total vehicle energy usage. Further, the impact of temperature, pressure, and humidity changes are shown to impact the local air density. This is needed to calculate aerodynamic drag on vehicles and has been found to play a significant role in the overall performance of a vehicle. Although the methodology of calculating air density varies only slightly throughout the literature, the application to transportation has still been limited. This study provides a means by which air density can be estimated for the contiguous U.S. using the NOAA MADIS dataset. These air density estimates were then used to determine vehicle performance in varying regions of the country to highlight the importance of consideration of weather variables when monitoring vehicle performance, but also to provide recommendations based on these locales upon fleet conversion to BEVs.

Moore, Amy↗

Performance of pumped counterflow virtual impactors to study aerosol interactions with laboratory generated warm clouds

Pumped Counterflow Virtual Impactors (PCVI) are designed to separate aerosols based on aerodynamic diameter, which is particularly useful for isolating cloud droplets and ice crystals from smaller particles. However, the PCVI transmission efficiency (TE) values reported in the literature show considerable variability, and little information is available on the TEs for cloud liquid droplets. Here, we determined the optimal flow conditions for PCVI sampling for different activation ratios from the MTU Pi-cloud chamber, highlighting the conditions that maximize droplet residual sampling while minimizing interstitial transmission. Even for a lower limit cloud activation ratio = 1:10, an add flow of 1.5 LPM achieves a residual fraction greater than 0.80, with a droplet TE of ∼15% for typical Pi-Chamber droplets with diameters between 3.5 to 10 µm. This framework can be adapted for field cloud measurements based on the cloud conditions of interest. TE for cloud droplets under flow conditions at which ∼99% of the unactivated submicron particles were removed was substantially lower between 8 and 16% than for supermicron dry particles (∼30 to 40% for 3 µm polystyrene latex spheres). In addition, we conducted a comparison of the performances of three similar PCVI units to assess repeatability for dry aerosols and cloud droplets. All three PCVIs performed similarly in rejecting submicron particles smaller than the desired cutoff diameter. One of the units showed lower TEs due to a misalignment of the internal orifice. We discuss a procedure that improved alignment and performance.

54 ENVIRONMENTAL SCIENCES↗

Preliminary Introduction of a Free Vortex Wake Method Into OpenFAST

Increasing wind turbine size can have substantial economic benefits. However, increasing wind turbine turbine size requires the use of models that accurately capture the aerodynamic response to large deflections and nonstraight blade geometries. Additionally, the installation of offshore floating turbines requires turbine models that can handle large rotor motion. Free vortex wake (FVW) methods are capable of modeling this type of complex physics while remaining computationally tractable to perform the many simulations necessary for turbine design. In this work, a FVW model is added to the National Renewable Energy Laboratory engineering tool OpenFAST to allow for the aerodynamic modeling of highly flexible turbines along with the aero-hydro-servo-elastic response capabilities of OpenFAST. Code implementation is not complete and thus no results are presented. However, areas of potential modeling improvement are discussed, such as modifications to the circulation calculation and the need for different FVW input model specifications when high-thrust cases are being modeled.

17 WIND ENERGY↗

OPEN2018 (continuation of GENSETS effort)

This project has demonstrated the key components and engineering principles to support a residential scale (1 to 2 kWe) recuperated Brayton cycle generator based upon a screw compressor and screw expander. This technical work is a continuation of the previously awarded ‘GENSETS’ program. The product goal has been to achieve a 40% fuel-to-electric LHV efficiency, an 80% overall CHP efficiency, emissions qualified to the California Air Resources Board standards, and at noise levels of 55 dB or less at 1 meter. Further, the product must operate with 8,000 hour service intervals and achieve a mean-time to overhaul of 90,000 hours. Lastly, and possibly most importantly, the product must meet demanding cost targets, exhibiting a factory cost well below $1,500/kWe. After extensive aerodynamic studies under the ‘GENSETS’ program, Brayton concluded that miniature turbomachinery could not achieve an efficiency consistent with the product’s system performance goal. Given compressor and turbine efficiency targets in the range of 78 to 81%, Brayton turned to the rotary screw machines. While the justification for a screw compressor over a conventional centrifugal compressor is well supported by industry experience, the high temperature expander represented the core technology advancement. To meet the extremely high efficiency goals, an all-ceramic rotary screw expander hot section was developed and has now been tested in the laboratory. This first-of-its-kind ceramic screw expander prototype was able to demonstrate aerodynamic efficiency in line with predictions. The test article was successfully run to full stress conditions so has also validated the mechanical design of such a unit. This has opened new avenues for the commercialization of high efficiency, small scale power generation. Interest in the technology has sparked several requests for alternate uses, an invitation to present at a screw machine conference, and continued interest from parties looking to develop a product in the spirit of the original ‘GENSETS’ goals.

42 ENGINEERING↗

kynema-fmb [SWR-23-07]

Kynema-FMB (FKA: Kynema) is an open-source performance portable flexible multibody (FMB) dynamics solver designed for time-domain simulations. While originally tailored for wind turbine structural dynamics, the formulation and implementation are those of a general flexible-multidbody dynamics solver that can readily be applied to a wide range of systems. Kynema was designed with a narrow focus, namely to provide a lightweight, fast, accurate FMD solver for coupling to computational-fluid-dynamics (CFD) codes, especially the CFD codes in the Kynema suite, for fluid-structure-interaction (FSI) simulations. Kynema-FMB is equipped to model systems that can be represented as a collection of beams and rigid bodies that are connected through constraints. Degrees of freedom are defined in the inertial/global frame of reference and include displacements and rotations (formally as rotation matrices, but stored as quaternions). The underlying formulation is built on a Lie-group time integrator designed for index-3 differential-algebraic equations, which is second-order accurate in time (Bruls et al., 2012). Beam models are based on geometrically exact beam theory and are discretized as high-order spectral finite elements similar to those in BeamDyn (Wang et al., 2017). The governing equations for a FMD system like a wind turbine constitute a highly nonlinear system of constrained partial-differential equations. Kynema-FMB uses analytical Jacobians in the nonlinear-system solves in each time step. Linear systems use sparse storage and several third-party sparse-linear-system solvers are enabled. Ill conditioning of linear systems is mitigated with preconditioning described in Bottasso et al, 2008. Kynema-FMB is integrated with a simple open-source controller (ROSCO). There is an application programming interface (API) for coupling to geometry-resolved CFD (like that in Sharma et al., 2023) and actuator-force CFD (like that in Kuhn et al., 2025). In the latter, for actuator-line models, Kynema-FMB includes an internal blade-element solver that depends on user-provided lookup tables for coefficients of lift and drag, i.e., aerodynamic polars. Kynema-FMB is written in C++ and leverages Kokkos and Kokkos-Kernels (KokkosEcosystem) as its performance portability layer enabling simulations on both CPU and GPU systems. The repository is equipped with extensive automated testing at the unit and regression/system levels. The following describes the high-level development objectives conceived for Kynema: *Kynema will follow modern software development best practices, including test-driven development (TDD), version control, hierarchical automated testing, and continuous integration (CI) for a robust development environment. *The core data structures are memory efficient and enable vectorization and parallelization at multiple levels. *Data structures are data-oriented to exploit methods for accelerated computing including high utilization of chip resources (e.g., single instruction multiple data (SIMD) instruction sets) and parallelization using GP-GPUs. *The computational algorithms incorporate robust open-source libraries for mathematical operations, resource allocation, and data management. *The API design considers multiple stakeholder needs and ensure integration with existing and future ecosystems for data science, machine learning, and AI. *Kynema-FMB is written in modern C++ and leverages Kokkos as its performance-portability library with inspiration from the kynema stack.

Sprague, MichaelA.↗

Development and Demonstration of a Fuel-Efficient, Class 8 Tractor & Trailer Engine System (SuperTruck II)

Navistar presents the SuperTruck II (ST II) Final Report to the Unites States Department of Energy (US DOE), which covers the five Budget Periods (BPs) from 10-1-2016 through 6-30-2022. For ST II, Navistar built on the achievements of the SuperTruck I (ST I) Program as a catalyst to continue critical research, design and development, testing, and operations to reach the ambitious goals of the ST II project. This approach allowed Navistar to continue contributing to the essential needs of our nation for safe, efficient, and cost-effective delivery of goods and services, as we reduced negative environmental effects and improved operational productivity. This document contains information specified in DOE F 4600.2, Final Scientific/Technical Report DOE F 241.3, B. SCIENTIFIC/TECHNICAL REPORTS, explaining how we met and exceeded program requirements. Throughout this Final Report, Navistar extracted information from documents prepared during the project that represent our management, design and development, building, and testing efforts to meet and exceed SuperTruck II project goals. Navistar followed Plan requirements to achieve / exceed Project Objectives: a) >100% improvement in vehicle freight efficiency (FE) (on ton-MPG basis) relative to 2009 baseline with stretch goal of 140% improvement [actual: 170%); b) >55% engine brake thermal efficiency (BTE) demonstrated in operational engine at a 65-mph cruise point on a dynamometer – ≥31% increase from 2009 baseline [actual: 55.20% of combined BTE) ; and c) development and implementation of commercially cost effective technologies (in terms of a simple payback). Technology selection / development path focused on developing technologies applicable for production within 3-year approach, while ensuring technology readiness and cost of ownership for end users. The Program was organized into five budget periods: Requirements / Technology Assessment and Initial Hardware Testing; Technology Development and Concept Readiness Demonstration; Technology Finalization and Validation Tractor / Trailer Fabrication, Integration and Commissioning Demonstration; and Fuel Economy (FE) and Brake Thermal Efficiency (BTE) and Program Completion. Leadership was provided by DOE, with tasks performed by laboratories (Argonne National Laboratory, Lawrence Livermore National Laboratory); partners at Bosch, TPI, Dana, and J.B. Hunt; , and support from University of Michigan and Clemson University. Navistar lead this team with Principal Investigator / Contracting Officer; Project Manager (PM); Vehicle, Engine, and Aftertreatment Engineers; Finance Manager, Technical Program Leads, and Legal/IP; and other key personnel. Work also included personnel in risk management; funding / budget / finance. Work involved analysis, development, testing, and down selection of individual/system engine, aftertreatment, and vehicle technologies, with integration of selected technologies into a prototype vehicle for demonstration of fuel-efficiency gain. Work also included component/integrated system level development of truck and trailer aerodynamics, base engine efficiency, advanced aftertreatment, combustion efficiency, waste heat recovery, hybrid powertrain, reduced rolling resistance, weight reduction, idle reduction, and driver feedback. As ST II progressed, Navistar performed computer-based modeling / simulations of technologies focused on the primary operational areas: Engine, Aftertreatment, and Vehicle. During the ST II Program, the COVID Virus outbreak unexpectedly challenged by the effects of, which affected staffing, scheduling, design, supplies, availability of materials, production procedures, and testing. The DOE responded by extending the program by three quarters to ensure that project tasks were completed for this vital project. Focus continued on analyzing, developing, testing, and down selecting individual-/system-level engine and vehicle technologies for integration of the final selected technologies into a prototype vehicle that would demonstrate fuel-efficiency gains made possible through these technologies. This included component/integrated system-level development of truck and trailer aerodynamics, base engine efficiency, advanced aftertreatment, combustion efficiency, waste heat recovery, solar power, distributed and intelligent vehicle power, hybrid powertrain, reduced rolling resistance, weight reduction, idle reduction, and driver feedback. Throughout the program, function, reliability, and performance at all levels were ensured through testing. Proof of this approach was demonstrated in multiple, on-road demonstrations: Scenario A (Flatland) Fuel Economy, Scenario B (Hilly) Fuel Economy, and City Cycle Tests. Other benefits derived from ST II included new/improved products, publications, patents, and next-step capabilities related to electric/hydrogen vehicles and autonomous driving.

Zukouski, Russ↗