Transfer of agricultural work operation profiles to a tractor test stand for exhaust emission evaluation

Ettl, Johannes; Bernhardt, Heinz; Pickel, Peter; Remmele, Edgar; Thuneke, Klaus; Emberger, Peter

doi:10.1016/j.biosystemseng.2018.10.016

Cited by 15 publications

(11 citation statements)

References 16 publications

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“…Tractors are known as the main energy source for various field applications in combination with different agricultural machinery and implements. During field operations, fuel consumption, work performance and negative environmental impacts are the most important tractor performance indicators [1][2][3]. Fuel consumption at various field operations depends on many factors, such as soil texture and structure, tractor size and its configuration, relationship of the tractor and implement, tillage speed, etc.…”

Section: Introductionmentioning

confidence: 99%

Estimation of tractor wheel slippage with different tire pressures for 4wd and 2wd driving systems

Janulevičius

Juostas

Pupinis

2019

Engineering for Rural Development

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The wheel slippage of agricultural tractors is a critical parameter for fuel consumption and field performance. Optimally it should be in the range of 8-12 % and should not exceed 15 %. Therefore, during assembling agricultural units, it is not enough to consider the traction characteristics, but also the recommended value of the slippage must be followed. Of the available solutions to decrease the tractor driving wheel slippage is to decrease the air pressure in the tires and increase the additional mass (ballast weight) of the tractor, avoid tilling soil that is too wet or too dry and choose the right implement, tillage speed and depth. The wheels' slippage could be reduced with a traction control and other relevant tractor systems. Agricultural/field applications require tractors with 4WD or 2WD driving systems. Engaging the four-wheel drive, when using the tractor for tillage operations, also can decrease the wheel slippage. In any case, the fuel consumption must be taken into consideration. For the theoretical calculation of the optimal tractor wheel slippage it is important to know the attraction factor dependence on the size of the traction force and the vertical load on the tires and the tire pressure indicators as well. However, literature analysis shows that known tractor wheel slippage determination mathematical modules do not take into consideration the tire inflation pressure. The goal of this study is to investigate the tire air pressure influence on the driving wheel slippage, tractive force and the traction coefficient for 4WD and 2WD driving systems of the tractor. With help of mathematical equations the traction force and wheel slippage coefficient dependencies on the air pressure in tractor tires are calculated. As well, according to the research result data, the wheel slippage forecasting methodology based on the numerical evaluation of the tire inflation pressure for 4WD and 2WD driving systems of the tractor is provided.

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Section: Introductionmentioning

confidence: 99%

Estimation of tractor wheel slippage with different tire pressures for 4wd and 2wd driving systems

Janulevičius

Juostas

Pupinis

2019

Engineering for Rural Development

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“…Driving cycles were created to simulate real traffic and allow comparison of only some specific values, even with different methodology, units and machinery. NRSC and NRTC tests (Ettl et al 2018) are used for tractors. Traction forces in connection with terramechanics was researched (Cutini and Bisaglia 2016), as well as the emissions and fuel consumption during real driving (Ince and Güler 2020) or during dynamometer simulation (Schlosser et al 2017).…”

Section: Resultsmentioning

confidence: 99%

Calculation model of the tractor transport set - Economic and environmental indicators

Kubín¹,

Pexa²,

Holúbek³

2021

Res. Agric. Eng.

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This contribution presents a calculation method of indicators in agricultural transport. The tractor Zetor Forterra 8641 with a silage trailer was used. Calculations were performed with various weights of transported material: 2.5, 3.6, 5.8, 7.4 and 9.0 tons. The model was created concerning significant parameters of the transport set, engine characteristics and route. It considered splitting of the route into elementary sections, in which important route parameters were regarded as constant. Indicators were defined in every section (fuel consumption, emissions, etc.) and overall values were calculated as a sum. The set with 7.4 t of load reached the lowest unit costs 20.62 CZK·tkm–1, transport output 79.51 tkm·h–1 and unit consumption 0.14 L·tkm–1. The set with the maximum load 9.0 t reached output 86.05 tkm·h–1 but unit costs were 20.68 CZK·tkm–1. Using the maximum capacity was not the most effective option. When the weight of a load increased (from 2.5 to 9.0 t), driving time extended from 0.28 to 0.46 h and hourly transportation output increased from 38.60 to 86.05 tkm·h–1, unit consumption decreased from 0.24 to 0.13 L·tkm–1. Total emissions significantly increased, but unit emissions decreased in average two times for each pollutant.

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“…For these reasons, this approach is far too simplistic and data misclassifications are not infrequent. More advanced rule-based algorithms were proposed for specific tractor operations (Ettl et al, 2018), and forage harvesters (Harmon et al, 2018;Zhang et al, 2017). Rule-based algorithms require knowledge from the experts and a reasonable amount of effort to design and implement effective rules for real-world data.…”

Section: Pag 3/27mentioning

confidence: 99%

“…15/27 field work states provide an insight of the portion of time where the tractor operated for field related activities, and it includes the time for actual work, headlands, field setting, and maintenance at field (Lovarelli et al, 2017). Headlands contribute to 24% of the entire field work state and this figure is aligned to that of Ettl et al (2018). Moreover, the time contribution of the marginal is less than 3%, which means that the defined work states can describe most of the tractor operations.…”

Section: Pag 13/27mentioning

confidence: 99%

Outlining the mission profile of agricultural tractors through CAN-BUS data analytics

Mattetti

Maraldi

Lenzini

et al. 2021

Computers and Electronics in Agriculture

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Transfer of agricultural work operation profiles to a tractor test stand for exhaust emission evaluation

Cited by 15 publications

References 16 publications

Estimation of tractor wheel slippage with different tire pressures for 4wd and 2wd driving systems

Estimation of tractor wheel slippage with different tire pressures for 4wd and 2wd driving systems

Calculation model of the tractor transport set - Economic and environmental indicators

Outlining the mission profile of agricultural tractors through CAN-BUS data analytics

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