Agricultural Industry Advanced Vehicle Technology: Benchmark Study for Reduction in Petroleum Use

Hoy, Roger M.; Rohrer, Rodney A.; Liska, Adam; Luck, Joe D.; Isom, Loren; Keshwani, Deepak R.

doi:10.2172/1166050

Cited by 20 publications

(27 citation statements)

References 30 publications

(19 reference statements)

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“…When obtaining the driveshaft torque, the inertial torque of the rotational inertias can be neglected, since the vehicle speed is maintained at a nearly constant value. The HSU stroke, which satisfies the HMT operation at point P of the third sub-shift gear, can be determined from equation (25) as follows Figure 13 shows the simulation results for the second ! third sub-shift by the proposed sub-shift control algorithm without clutch speed synchronization.…”

Section: Simulation and Discussionmentioning

confidence: 99%

“…Since the PTO workings require a constant vehicle speed, 25 the forward clutch pressure is controlled only to transmit the same torque during the sub-shift. The forward clutch pressure to transmit T DS can be obtained as…”

Section: Forward Clutch Pressure Controlmentioning

confidence: 99%

“…When the tractor works using the PTO, in general, the engine and vehicle speeds need to be maintained at a constant value. 25 The HSU stroke i st , which maintains the demanded engine speed for the given vehicle speed, can be obtained. The speed ratio SR for the second and third sub-shift gears is derived using the HSU stroke as follows…”

Section: Hsu Stroke Controlmentioning

confidence: 99%

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Development of a new sub-shift schedule and control algorithm for a hydro-mechanical transmission

Ahn

Choi

Son

et al. 2016

Advances in Mechanical Engineering

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In this study, a new sub-shift schedule was proposed for a hydro-mechanical transmission. To develop the sub-shift schedule, a network analysis was performed by considering the hydrostatic unit loss and mechanical component losses. In the new sub-shift schedule, the sub-shift gear can be selected with respect to the demanded wheel torque and vehicle speed, which provides improved system efficiency for the given vehicle operating condition. Since the sub-shift can only be carried out at a speed ratio where the off-going and on-coming clutch speeds are synchronized in the existing subshift control, a sub-shift control algorithm without the clutch speed synchronization was proposed to apply the new subshift schedule using the forward clutch pressure and hydrostatic unit stroke control. The performance of the sub-shift control algorithm without the clutch speed synchronization was evaluated by the simulation and experiment. It was found from the simulation and experimental results that the sub-shift can be achieved, showing an acceptable peak-topeak torque variation in the driveshaft.

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Section: Simulation and Discussionmentioning

confidence: 99%

Section: Forward Clutch Pressure Controlmentioning

confidence: 99%

Section: Hsu Stroke Controlmentioning

confidence: 99%

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Development of a new sub-shift schedule and control algorithm for a hydro-mechanical transmission

Ahn

Choi

Son

et al. 2016

Advances in Mechanical Engineering

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“…Heavy-duty construction and agricultural vehicles also have an environmental impact. In Agricultural Industry Advanced Vehicle Technology: Benchmark Study for Reduction in Petroleum Use [11], the current trends in increasing diesel efficiency in the farm sector are explored. Figure 1 shows the diesel demand in the United States, highlighting that in the agricultural and construction machinery field, the demand has remained relatively constant since 1985, representing a significant portion of the total fuel consumption.…”

Section: Introductionmentioning

confidence: 99%

Trends and Hybridization Factor for Heavy-Duty Working Vehicles

Somà¹

2017

Hybrid Electric Vehicles

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Reducing the environmental impact of ground vehicles is one of the most important issues in modern society. Construction and agricultural vehicles contribute to pollution due to their huge power trains, which consume a large amount of petrol and produce many exhaust emissions. In this study, several recently proposed hybrid electric architectures of heavy-duty working vehicles are presented and described. Producers have recently shown considerable attention to similar research, which, however, are still at the initial stages of development. In addition, despite having some similarities with the automotive field, the working machine sector has technical features that require specific studies and the development of specific solutions. In this work, the advantages and disadvantages of hybrid electric solutions are pointed out, focusing on the greater electromechanical complexity of the machines and their components. A specific hybridization factor for working vehicles is introduced, taking into account both the driving and the loading requirements in order to classify and compare the different hybrid solutions.

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“…The agricultural sector is the largest consumer of offhighway diesel, accounting for 5.4% of the total use in the U.S. in 2010 (Hoy et al, 2014). Considering that tractors are the primary power unit for most mechanized agricultural operations, much of the focus on increasing efficiency has been directed toward tractors.…”

mentioning

confidence: 99%

Fuel Consumption Models for Tractor Test Reports

Kocher¹,

Smith²,

Hoy³

et al. 2017

Transactions of the ASABE

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Abstract. Five models for estimating fuel consumption for agricultural tractors with partial drawbar loads were compared. Data were collected from eight John Deere tractors, JD 7230R (e23), 7250R (e23), 7270R (e23), 7290R (e23), 8320R (16 speed), 7290R (IVT), 8345RT (IVT), 8370R (IVT), on the drawbar test track at the Nebraska Tractor Test Lab. The tractors were tested with seven load levels per speed at three different travel speeds as close as possible to 7.5, 10, and 13 km h-1. The IVT tractors were operated in auto mode, and the geared tractors were shifted up three gears and throttled back to the same travel speeds as obtained with the original gear (before shifting up) at maximum drawbar power. The seven loads were selected at 30%, 40%, 50%, 60%, 70%, 75%, and 80% of the drawbar pull at maximum power and rated engine speed at the selected travel speed. Model 1 (fuel consumption as a linear function of drawbar power on concrete), currently used in OECD Code 2, Section 4.4.8, resulted in a separate equation for each speed tested. When regression mean square errors were used for statistical comparison of the five fuel consumption models, model 5 (fuel consumption as a linear function of drawbar power and travel speed on concrete, and engine speed) was not significantly different from the model currently used in OECD Code 2, Section 4.4.8 (model 1, fuel consumption as a linear function of drawbar power on concrete, with separate equations specific to the three speeds tested). The simplest model (model 2), which used a single equation for fuel consumption as a linear function of drawbar power on concrete over the range of speeds tested, had significantly higher regression mean square errors compared to model 1 for half of the eight tractors tested. Model 5 (fuel consumption as a linear function of drawbar power and travel speed on concrete, and engine speed) was determined to be the best of the five models for estimating fuel consumption, with a single equation applicable over the range of speeds tested. Model 3 (fuel consumption as a linear function of drawbar power and travel speed on concrete) provided a statistically equivalent fuel consumption estimate to model 5 without the drawback of requiring an input value for engine speed. Keywords: Drawbar power, Engine speed, Fuel consumption, Model, Partial drawbar loads, Tractors, Travel speed.

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Agricultural Industry Advanced Vehicle Technology: Benchmark Study for Reduction in Petroleum Use

Cited by 20 publications

References 30 publications

Development of a new sub-shift schedule and control algorithm for a hydro-mechanical transmission

Development of a new sub-shift schedule and control algorithm for a hydro-mechanical transmission

Trends and Hybridization Factor for Heavy-Duty Working Vehicles

Fuel Consumption Models for Tractor Test Reports

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