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PACE: Producing Algae for Co-Products and Energy (Final Report)

The PACE (Producing Algae for Co-Products and Energy) consortium was comprised of scientists from national laboratories (Los Alamos National Laboratory, Pacific Northwest National Laboratory), research institutions (New Mexico Consortium), academic institutions (Arizona State University, Colorado School of Mines, Colorado State University, Washington State University) and private companies (Reliance Industries, PanPacific, Genifuel and Sonosop) dedicated to making process improvements in algal biotechnology, with an emphasis on renewable fuels and co-products from biomass. The scope of work was focused on improving algal cultivation and processing to achieve an overall energy return on investment (EROI) >3, a carbon index less than 55 grams carbon dioxide per megajoule (gCO2/MJ) and a nearly two-fold reduction in fuel cost to ≤$5 per gallon of gasoline equivalent (gge). The PACE project was originally focused on using two strains of Chlorella sorokiniana (Cs1412 and Cs1230), but later grew to encompass marine strains of Nannochloropsis and algal production strains from Reliance Industries Limited (RIL).

09 BIOMASS FUELS↗

Land-Based Wind Market Report: 2021 Edition

The U.S. Department of Energy's 2021 edition of its land-based wind market report provides an overview of key trends in the U.S. wind power market, with a focus on 2020. You can find a report, data file and presentation on the Files tab, below. Additionally, several data visualizations are available on the Visualizations tab. Highlights of this year’s update include: -Wind comprises a growing share of electricity supply: U.S. wind power capacity grew at a record pace in 2020, with 25 billion dollars invested in 16.8 GW of capacity. Wind energy output rose to account for more than 8% of the entire nation’s electricity supply, and is more than 20% in 10 states. At least 209 GW of wind are seeking transmission interconnection; 61 GW of this capacity are offshore wind and 13 GW are hybrid plants that pair wind with storage or PV. -Wind project performance has increased over time: The average capacity factor among recently built projects was over 40%, considerably higher than projects built earlier. The highest capacity factors are seen in the interior ‘wind belt’ of the country. -Turbines continue to get larger: Improved plant performance has been driven by larger turbines mounted on taller towers and featuring longer blades. In 2010, no turbines employed blades that were 115 meters in diameter or larger, but in 2020, 91% of newly installed turbines featured such rotors. Proposed projects indicate that total turbine height will continue to rise. -Low wind turbine pricing has pushed down installed project costs over the last decade: Wind turbine prices are averaging 775–850 dollars/kW. The average installed cost of wind projects in 2020 was 1,460 dollars/kW, down more than 40% since the peak in 2010, though stable for the last three years. The lowest costs were found in Texas and the (non-ISO) West. -Wind energy prices remain low, around 20 dollars/MWh in the interior of the country: After topping out at 70 dollars/MWh for power purchase agreements (PPAs) executed in 2009, the national average price of wind PPAs has dropped. In the interior ‘wind belt’ of the country, recent pricing is around 20 dollars/MWh. In the West and East, prices tend to average 30 dollars/MWh or more. These prices, which are possible in part due to federal tax support, fall below the projected future fuel costs of gas-fired generation. -Wind PPA prices are often attractive compared to wind’s grid-system market value: The value of wind in wholesale power markets is affected by the location of wind plants, their hourly output profiles, and how those characteristics correlate with real-time electricity prices and capacity markets. The market value of wind declined in 2020, following natural gas prices lower and averaging under 15 dolalrs/MWh in ERCOT, MISO, NYISO and SPP; higher values were seen in CAISO, ISO-NE and PJM. -The average levelized cost of wind energy is down to 33 dollars/MWh: Levelized costs, which exclude the impacts of federal tax incentives, vary across time and geography, but the national average stood at 33 dollars/MWh in 2020—down substantially historically, though consistent with the previous two years. Levelized costs were lowest in ERCOT, SPP, and the (non-ISO) West. -The health and climate benefits of wind in 2020 were larger than its grid-system value, and the combination of all three far exceeds the current levelized cost of wind: Wind generation reduces power-sector emissions of carbon dioxide, nitrogen oxides, and sulfur dioxide. These reductions, in turn, provide public health and climate benefits that vary regionally, but together are economically valued at an average of 76 dollars/MWh-wind nationwide in 2020. -The domestic supply chain for wind equipment is diverse: For wind projects recently installed in the U.S., domestically manufactured content is highest for nacelle assembly (>85%), towers (60-75%), and blades and hubs (30-50%), but is much lower for most components internal to the nacelle.

17 WIND ENERGY↗

Land-Based Wind Market Report: 2022 Edition

The U.S. Department of Energy's 2022 edition of its Land-Based Wind Market Report provides an overview of key trends in the U.S. wind power market, with a focus on 2021. You can find a report, data file and presentation on the Files tab, below. Additionally, several data visualizations are available on the Visualizations tab. Despite ongoing supply chain challenges, wind energy in 2021 continued to see strong growth, technology improvements, and low prices in the U.S. Key highlights include: Wind comprises a growing share of electricity supply: U.S. wind power capacity grew at a strong pace in 2021, with the 13.4 GW of new additions representing a $\$20$ billion investment and 32% of all newly added U.S. generation capacity. Wind energy output rose to account for more than 9% of the entire nation’s electricity supply. At least 247 GW of wind are seeking transmission interconnection; 77 GW of this capacity are offshore wind and 19 GW are hybrid plants that pair wind with storage or solar PV. Wind project performance has increased over the decades: The average capacity factor among recently built projects was nearly 40%, considerably higher than projects built earlier. The highest capacity factors are seen in the interior ‘wind belt’ of the country. Turbines continue to get larger: Improved plant performance has been driven by larger turbines mounted on taller towers and featuring longer blades. In 2011, no turbines employed blades that were 115 meters in diameter or larger, but in 2021, 89% of newly installed turbines featured such rotors. Proposed projects indicate that total turbine height will continue to rise. Low wind turbine pricing has pushed down installed project costs over the last decade: Wind turbine prices averaged $\$800$–$\$950$/kW in 2021, a 5% to 10% increase from the year prior but substantially lower than in 2010. The average installed cost of wind projects in 2021 was $\$1,500$/kW, down more than 40% since the peak in 2010, though relatively stable in recent years. The lowest costs were found in Texas and the (non-ISO) West. Wind energy prices are on the rise, but generally remain low, around $\$20$/MWh in the interior of the country with higher prices in the West and East. After topping out above $\$75$/MWh for power purchase agreements (PPAs) executed in 2009, the national average price of wind PPAs has dropped—though supply-chain pressures have resulted in increased prices in recent years. In the interior ‘wind belt’ of the country, recent pricing is around $\$20$/MWh. In the West and East, prices tend to average above $\$30$/MWh. These prices, which are possible in part due to federal tax support, fall below the projected future fuel costs of gas-fired generation. Wind PPA prices are often attractive compared to wind’s grid-system market value: The value of wind in wholesale power markets is affected by the location of wind plants, their hourly output profiles, and how those characteristics correlate with real-time electricity prices and capacity markets. The market value of wind increased in 2021, averaging $\$16$/MWh in MISO, $\$19$/MWh in SPP, $\$23$/MWh in NYISO, $\$31$/MWh in ERCOT, $\$33$/MWh in PJM, $\$44$/MWh in ISO-NE, and $\$48$/MWh in CAISO. The average levelized cost of wind energy was $\$32$/MWh for plants built in 2021: Levelized costs, which exclude the impacts of federal tax incentives, vary across time and geography. The national average stood at $\$32$/MWh in 2021—down substantially historically, though relatively stable in recent years. Levelized costs were lowest in ERCOT, SPP, and the (non-ISO) West. The health and climate benefits of wind in 2021 were larger than its grid-system value, and the combination of all three far exceeds the current levelized cost of wind: Wind generation reduces power-sector emissions of carbon dioxide, nitrogen oxides, and sulfur dioxide. These reductions, in turn, provide public health and climate benefits that vary regionally, but together are economically valued at an average of over $\$90$/MWh-wind for plants built in 2021.

17 WIND ENERGY↗

Optimizing Hydronic Heating for Comfort and Performance in Multifamily Housing

Inefficient control settings in multifamily boilers often lead to substantial energy and cost penalties. To address this, a Fault Detection and Diagnostic (FDD) tool was developed to automate data analysis and identify operational faults such as suboptimal outdoor temperature sensor placement, misconfigured outdoor air reset (OAR) curves, excess boiler cycling, and domestic hot water (DHW) setpoint errors. By comparing pre- and post-implementation periods and applying engineering models, the tool quantifies energy savings and reduces manual analysis time by over 90%. Testing on over 100 monitored sites and a targeted subset of 12 buildings showed an average 11% energy savings from remote optimization; further validation across 19 OAR curve changes confirmed the tool’s accuracy, predicting actual savings within ±5% for most cases. Simple payback can be under three years for many multifamily buildings, though rising hardware, labor, and fuel costs create uncertainties, and decarbonization goals increasingly shift focus to electrification. The FDD tool remains invaluable for optimizing existing boilers, enhancing future electrification measures, and adapting to new technologies by refining building load estimates. In doing so, it supports both near-term efficiency and long-term transitions to low-carbon alternatives, ensuring buildings achieve substantial cost and energy benefits throughout their system lifecycles.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Solar Thermal Energy Planner (STEP 1): A New Decision Support Tool for Solar Industrial Process Heat Applications

Solar thermal technologies are a promising technology to supply low-cost thermal energy to industrial processes, but there are often significant barriers to entry to industrial owners considering these technologies for their energy demands. To overcome this barrier and convey economic value to customers, NREL and Sandia National Laboratories developed Solar Thermal Energy Planner (STEP 1), a new web-based decision support tool for solar industrial process heat systems. At SolarPACES 2024, the STEP 1 tool was still under development; progress, methodologies, and a preliminary case study was presented. With the STEP 1 tool launch in May 2025, in this work, the initial version of the full public tool will be presented with demonstrations of its capabilities using a few case studies. First, the user's process heat needs such as location, process media (e.g., steam, air), process temperature, land availability, electricity and fuel costs, among other parameters. STEP 1 features a mapping interface that allows users to draw land and roof boundaries. The process media and temperature inform technology selection criteria modules that determine the appropriate solar thermal collection technologies, as well as congruent heat transfer media (e.g., hot water, oil, salt). Once the solar thermal technology selected, its nominal thermal production for the given site is characterized using NREL's System Advisor Model (SAM). Then, a modified version of NREL's REopt optimal sizing and dispatch optimization tool determines cost-optimal sizing. Within minutes, the user receives the results of the technoeconomics analysis, including the size and performance of the cost-optimal solar-plus-storage system. The cost of the system is compared to business-as-usual (e.g., an existing, standalone natural gas boiler). Users can download key results to store for sensitivity analyses. Examples of flat plate collector, parabolic trough, and molten salt tower applications with and without PV hybridization for different industrial facility types are presented in this work. The STEP 1 tool aims to reduce barriers to the adoption of solar heating solutions stemming from a lack of familiarity and technical background with solar system design options and costs among industry stakeholders.

14 SOLAR ENERGY↗

Pseudospectral convex optimization for on-ramp merging control of connected vehicles

It can be a daunting task for human drivers to merge into highways because of the intricate vehicle negotiations and potential risk within limited time and space. Connected vehicle (CV) technologies could be a solution to this problem and offer many benefits to the road safety, traffic mobility, and energy efficiency. However, real-time optimal control of CVs is still an open challenge, due to the nonlinear vehicle dynamics, non-convex fuel consumption model, and highly dynamic uncertain inter-vehicle interactions. To tackle these issues, a novel real-time optimal control approach that balances the computational efficiency and solution optimality is proposed for the purpose of onboard application. To this end, the pseudospectral collocation method is integrated with a sequential convex programming approach to develop two new optimization algorithms, which are implemented within a model predictive control (MPC) framework to allow for real-time generation of optimal merging speed profiles. One algorithm leverages the line search technique to improve convergence, and the other benefits from the trust region method for better computational efficiency. The optimality and convergence process of both proposed algorithms are investigated by comparing their solutions with a popular non-linear solver. Furthermore, simulation results show that the proposed methods outperform the benchmark in terms of computational cost, fuel consumption, and traffic efficiency. In particular, the proposed fuel-economy merging rule can save 57.1% fuel consumption on average on four different traffic volumes. Meanwhile, the proposed optimal control algorithms can reduce 2.2% travel time on average comparing to the “first-in-first-out” merging rule.

33 ADVANCED PROPULSION SYSTEMS↗

Fuzzified PaCcET for Economic-Emission Scheduling of Microgrids

In this paper, a new approach is proposed to solve a multi-objective economic-emission scheduling problem in microgrids (MGs) by simultaneously minimizing the energy and emission costs of the MG with various distributed energy resources (DERs). The proposed approach is an extension of a computationally effective multiobjective optimization technique, Pareto concavity elimination transformation (PaCcET). The proposed approach, referred to as Fuzzified-PaCcET, employs a fuzzy logic controller to dynamically revise crossover and mutation rates in the original PaCcET leading to the faster convergence of the solution. The proposed approach finds the best Pareto front, also referred to as a Non-dominated set (NDS) of solutions, instead of finding a single optimal solution. In order to find the solutions on concave areas of the Pareto front, an iterative objective space transformation is performed in the PaCcET algorithm to allow a linear combination of objective functions (in the transformed objective space). The proposed Fuzzified-PaCcET-based scheduling is implemented on a MG with various dispatchable and non-dispatchable DERs to find the set of optimal solutions according to the total fuel cost of DERs, as well as the most optimum environmental cost. In order to extract the best compromise solution (BCS) among NDS of solutions, a fuzzy-based method is implemented. The comparison of the simulation results of the Fuzzified-PaCcET with that of PaCcET shows that Fuzzified-PaCcET can generate better solution with less computational burden.

Gautam, Mukesh↗

Fuzzified PaCcET for Economic-Emission Scheduling of Microgrids

In this paper, a new approach is proposed to solve a multi-objective economic-emission scheduling problem in microgrids (MGs) by simultaneously minimizing the energy and emission costs of the MG with various distributed energy resources (DERs). The proposed approach is an extension of a computationally effective multiobjective optimization technique, Pareto concavity elimination transformation (PaCcET). The proposed approach, referred to as Fuzzified-PaCcET, employs a fuzzy logic controller to dynamically revise crossover and mutation rates in the original PaCcET leading to the faster convergence of the solution. The proposed approach finds the best Pareto front, also referred to as a Non-dominated set (NDS) of solutions, instead of finding a single optimal solution. In order to find the solutions on concave areas of the Pareto front, an iterative objective space transformation is performed in the PaCcET algorithm to allow a linear combination of objective functions (in the transformed objective space). The proposed Fuzzified-PaCcET-based scheduling is implemented on a MG with various dispatchable and non-dispatchable DERs to find the set of optimal solutions according to the total fuel cost of DERs, as well as the most optimum environmental cost. In order to extract the best compromise solution (BCS) among NDS of solutions, a fuzzy-based method is implemented. The comparison of the simulation results of the Fuzzified-PaCcET with that of PaCcET shows that Fuzzified-PaCcET can generate better solution with less computational burden.

42 ENGINEERING↗

Assessment of Light-Duty Plug-in Electric Vehicles in the United States, 2010 – 2021

The number of plug-in electric vehicles (PEVs) sold in the United States has consistently grown since 2010, reaching 4% of the light-duty vehicle market in 2021. This report examines how the characteristics for these PEVs has changed over this decade, evaluating range, energy efficiency, costs, and performance. Given the vehicle characteristics, this report estimates miles driven, electricity consumption, petroleum reduction, and greenhouse gas emissions attributable to electric vehicles. This report also explores vehicle manufacturing and battery production, considering supply chains from battery cells to assembly. Over 2.1 million PEVs have been sold in the United States through December 2021, with 1.3 million of these all fully-electric battery electric vehicles (BEV), and 800,000 plug-in hybrid electric vehicles (PHEV) which have the capability of using gasoline. The sales-weighted average range for BEVs reached 290 miles in 2021 and 28 miles for PHEVs. We estimate that electric vehicles have driven 68 billion miles on electricity since 2010, thereby reducing national gasoline consumption by 0.54% in 2021 and 2.5 billion gallons cumulatively through 2021. In 2021, PEVs used 6.1 terawatt-hours of electricity to drive 19.1 billion miles, offsetting 700 million gallons of gasoline. We find that this fuel switching reduced consumer fuel costs by $1.3 billion in 2021. Since 2010, 65% of PEVs sold in the United States have been assembled domestically, and over 110 gigawatt-hours of lithium-ion batteries have been installed in vehicles to date.

25 ENERGY STORAGE↗

Primer on the Cost of Marine Fuels Compliant with IMO 2020 Rule

This report aims to provide information for owners and operators of U.S. ocean-going marine cargo vessels on the cost of different approaches to compliance with the IMO mandate to reduce the sulfur content of marine fuels (outside emission control areas) to no more than 0.5%. The IMO 2020 rule came into effect on January 1, 2020. The report discusses a suite of options for compliance including low-sulfur petroleum-based fuels and alternative fuels. Since fuel prices are a primary factor in determining the cost of the various alternatives, the document also includes a discussion of the main drivers of marine fuel prices. The cost analysis compares the average annual costs (capital and fuel) out to 2050 of each compliance approach under alternative scenarios regarding fuel prices, policy, and technology innovation. The cost calculations focus on representative U.S. fleet vessels for containership and tanker types. Even though the analysis focuses on average cost of approaches to comply with IMO 2020, the comparison of approaches also acknowledges other benefits or risks including fuel price risk and the contribution of the approach to achieving other potential environmental performance objectives or regulations.

02 PETROLEUM↗

The Challenge Ahead: A Critical Perspective on Meeting U.S. Growth Targets for Sustainable Aviation Fuel

With demand for jet fuel expected to more than double by 2050 and triple by 2070, continued and accelerated efforts to decarbonize the global aviation sector are needed to curtail rising emissions and avert the worst outcomes of climate change. In response to this call-to-action, the United States has unveiled the Sustainable Aviation Fuel (SAF) Grand Challenge, which seeks to expedite the development of alternative fuel pathways that offer a minimum of a 50% reduction in life cycle greenhouse gas emissions compared to conventional jet fuel. However, there is growing concern on whether sufficient biomass will be readily available to satisfy the projected sharp rise in demand for SAF. Carbon dioxide point-source emissions combined with rising supply from direct air capture efforts have the potential to complement and offset any supply gaps for biomass-derived SAF and other use cases. Independent of the chosen feedstock and conversion technology, numerous challenges persist across SAF production in seeking to drive down fuel cost and carbon intensity. To hit the 2030 target of 3 billion gal/yr, this means about a 100% compound annual growth rate in volumetric SAF production (about 130 times scale-up) will need to be realized. To achieve the stretch goal of 35 billion gallons of SAF per year by 2050, volumetric production must increase by a factor of 12 from the 3-billion-gal/year 2030 target of SAF Grand Challenge. The comparatively longer runway for 2050 combined with significant production volume growth suggests a more inclusive "all-hands-on-deck"-style approach will likely play a role. A key component in success lies in the coordinated research, development, demonstration, and deployment efforts by multiple federal agencies and industry partnerships.

09 BIOMASS FUELS↗

Toward sustainable, cell-free biomanufacturing

Industrial biotechnology is an attractive approach to address the need for low-cost fuels and products from sustainable resources. Unfortunately, cells impose inherent limitations on the effective synthesis and release of target products. One key constraint is that cellular survival objectives often work against the production objectives of biochemical engineers. Additionally, industrial strains release CO2 and struggle to utilize sustainable, potentially profitable feedstocks. Cell-free biotechnology, which uses biological machinery harvested from cells, can address these challenges with advantages including: (i) shorter development times, (ii) higher volumetric production rates, and (iii) tolerance to otherwise toxic molecules. In this review, we highlight recent advances in cell-free technologies toward the production of non-protein products beyond lab-scale demonstrations and describe guiding principles for designing cell-free systems. Specifically, we discuss carbon and energy sources, reaction homeostasis, and scale-up. Expanding the scope of cell-free biomanufacturing practice could enable innovative approaches for the industrial production of green chemicals.

59 BASIC BIOLOGICAL SCIENCES↗

Optimal operation of multi-plant steam district heating systems for enhanced efficiency and sustainability

Despite their crucial role in supplying heat and power to universities, industries, and healthcare facilities, many steam-based district heating systems rely on outdated control methods. Among these, multi-central plant districts are particularly challenging due to the complexities of coordinating multiple plants, optimizing load distributions, and managing system downtime. In response, new operational strategies are developed to enhance the efficiency and sustainability of steam districts while utilizing existing resources. These strategies include reducing plant operational pressure without compromising the reliable supply to buildings and optimizing load allocation across multiple plants. The load allocation considers boiler part-load efficiency, runtime, network losses, and building pressure set points, and is compared with traditional multi-boiler controls. To support this exploration, new dynamic Modelica models are developed. In addition, methods to reduce modeling complexities are incorporated, enhancing their suitability for practical applications. A holistic district-wide analysis using a real university case study demonstrates a 4.7% fuel savings by lowering boiler operational pressure from 900 kPa to 600 kPa, along with a 13.3% reduction in condensation losses across the distribution network. Furthermore, the load allocation approach results in a 13.1% reduction in fuel consumption during peak winter periods and 15.3% during shoulder periods, with corresponding decreases in carbon emissions and fuel costs. This approach can also save maintenance costs by reducing the boiler runtime by 49.6%. In conclusion, this research underscores the benefits of retrofitting aging steam district heating systems, offering immediate operational improvements by enhancing efficiency, meeting regulatory compliance, and extending infrastructure lifespans while delaying costly overhauls.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Optimal charging scheduling and management for a fast-charging battery electric bus system

Herein we discuss how battery electric buses (BEBs) are rapidly being embraced by public transit agencies because of their environmental and economic benefits. To address the problems of limited driving range and time-consuming charging for BEBs, manufacturers have developed rapid on-route charging technology that utilizes typical layovers at terminals to charge buses in operation using high power. With on-route fast-charging, BEBs are as capable as their diesel counterparts in terms of range and operating time. However, on-route fast-charging makes it more challenging to schedule and manage charging events for a BEB system. First, on-route fast-charging may lead to high electricity power demand charges. Second, it may increase electricity energy charges because of charging that occurs during on-peak hours. Without careful charging scheduling and management, on-route fast-charging may significantly increase fuel costs and reduce the economic attractiveness of BEBs. The present study proposes a network modeling framework to optimize the charging scheduling and management for a fast-charging BEB system, effectively minimizing total charging costs. The charging schedule determines when to charge a BEB, while the charging management strategically controls the actual charging power. Charging costs include both electricity demand charges and energy charges. The charging scheduling and management problem is first formulated as a nonlinear nonconvex program with time-continuous variables. A discretizing method and a linear reformulation technique are then adopted to reformulate the model as a linear program, which can be easily solved using off-the-shelf solvers, even for large-scale problems. Finally, the model is demonstrated with extensive numerical studies based on two real-world bus networks. The results demonstrate that the proposed model can effectively determine the optimal charging scheduling and management for a fast-charging BEB system, which carries the potential for use in large-scale real-world bus networks.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Estimating the Rebound Effect of the U.S. Road Freight Transport

The United States (U.S.) road freight sector has continued to grow over recent decades. Growth in road freight could result in more fuel consumption and hence increased greenhouse gas emissions. Policymakers have attempted to manage the growth of energy usage through improved fuel economy based on technological advances. However, such improvements may not lead to anticipated goals because of the rebound effect, where improvements in energy efficiency trigger more travel and energy consumption that offsets energy savings. Thus, this study aims to determine the potential rebound effect from improved energy efficiency in the U.S. road freight sector. Eight fuel cost models are applied and asymmetric price response is incorporated in estimating the U.S. road freight sector’s rebound effect from 1980 to 2016. In addition, a recently developed data envelopment analysis is applied to determine the annual rebound effect in the road freight sector. The results suggest that, after accounting for the asymmetric price response, the average rebound effect of the U.S. road freight sector ranges from 6.9% to 8.8%, a level considerably less than that found for several industrialized countries and emerging economies. However, a considerable increase in the rebound effect has been seen in more recent years. Here, the findings suggest that overlooking the rebound effect in environmental policies could impede the goal of reducing total energy consumption and accompanying emissions. Policymakers should incorporate the rebound effect from efficiency enhancement in policy development and utilize some potential programs to reduce the adverse influence of rebound effect in related policies.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Formulation and Experimental Validation of an Agricultural Implement-Only MPR System for Maximum Compatibility with Existing Agricultural Tractors

Tightening emissions regulations and rising fuel costs have driven a desire across many industries for more efficient actuation systems. This is particularly true of the agricultural sector. An extremely common arrangement in this sector is the tractor and implement pairing, in which actuators on an implement are powered by a hydraulic supply system on the towing tractor. This arrangement complicates the development of energy efficient hydraulic systems, as many new system designs require modification of both machines to reap efficiency benefits. Past work by the authors’ team has demonstrated great potentials for Multi-Pressure-Rail (MPR) technology involving both the tractor and implement subsystems. However, applicability of this MPR technology in a more realistic scenario where only one vehicle is equipped with such technology was not addressed. This work proposes an implementation of the MPR technology to an agricultural planter that allows significant savings, while only modifying the implement machine. This is done by manipulating the load sense network of a stock tractor to set system pressures to those required by the MPR system. This greatly reduces the barrier to implementation of MPR technology in agriculture. The work begins by outlining the reference machine for the system, then reviews the MPR system working principle. After this, the proposed expansion to the MPR concept is laid out and applied to the reference system. Finally, experimental validation is carried out, demonstrating up to a 35% reduction in system power consumption when paired with a state of the art, double-LS System tractor, and 15% with a single-LS System tractor.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Implement-Only Implementation of a Multi Pressure Rail System to an Agricultural Planter

Tightening emissions regulations and rising fuel costs have driven a desire across many industries for more efficient actuation systems. This is particularly true of the agricultural sector. An extremely common arrangement in this sector is the tractor and implement pairing, in which actuators on an implement are powered by a hydraulic supply system on the towing tractor. This arrangement complicates the development of energy efficient hydraulic systems, as many new system designs require modification of both machines to reap efficiency benefits. Past work by the authors’ team has demonstrated great potentials for Multi-Pressure-Rail (MPR) technology involving both the tractor and implement subsystems. However, applicability of this MPR technology in a more realistic scenario where only one vehicle is equipped with such technology was not addressed. This work proposes an implementation of the MPR technology to an agricultural planter that allows significant savings, while only modifying the implement machine. This is done by manipulating the load sense network of a stock tractor to set system pressures to those required by the MPR system. This greatly reduces the barrier to implementation of MPR technology in agriculture. The work begins by outlining the reference machine for the system, then reviews the MPR system working principle. After this, the proposed expansion to the MPR concept is laid out, and applied to the reference system. Finally, experimental validation is carried out, demonstrating on average 37% reduction in system power consumption.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗