Rule-based power distribution in the power train of a parallel hybrid tractor for fuel savings

Lee, Hyun-Sub; Kim, Jin-Seong; Park, Yeong-il; Cha, Sungdeok

doi:10.1007/s40684-016-0030-6

Cited by 23 publications

(7 citation statements)

References 6 publications

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“…Since ARET often work in an unmanned environment, in order to ensure the good driving performance of an ARET, two stages of control were adopted based on the traditional power following strategy [26,27]: the first stage is the pure electric drive stage, and the power consumption mode is the CD stage, where the SOC value of the battery continues to decrease from the initial value to the lower threshold of SOC; in the second stage, the range extender starts to work. In order to avoid frequent engine starts and stops, which may cause the SOC of the lithium battery pack to be in a low state for a long time, leading to the phenomenon of discharge occurring in some working conditions, where the range extender continues to open and enters the CS stage of the power maintenance mode.…”

Section: Rule-based Energy Management Strategymentioning

confidence: 99%

Energy Management of Sowing Unit for Extended-Range Electric Tractor Based on Improved CD-CS Fuzzy Rules

Wang

Xing

et al. 2023

Agriculture

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In order to ensure the continuity and endurance mileage requirements during sowing operations, it is necessary to establish accurate modeling for the working condition of the electric tractor sowing unit by adopting a reasonable energy management strategy and realizing accurate energy prediction. The existing electric tractor sowing unit battery energy management strategy is not optimal since it is mostly based on extensive rules. In this paper, according to the requirements of the sowing conditions, a precise model of electric energy consumption in the sowing cycle was established and an energy management strategy of sowing unit of extended-range electric tractor with power CD-CS was proposed. Fuzzy control rules of the dynamic SOC correction factor were established in the battery maintenance stage, and the NSGA-II algorithm was used to optimize the fuzzy control rules to optimize the battery charging and discharging efficiency. A hardware-in-the-loop simulation test platform was built, and the proposed CD-CS strategy was compared with the fuzzy improvement strategy. The simulation results show that the proposed fuzzy improvement strategy extended the battery life of the power consumption stage by 2131.9 s, which is a significant improvement. The field practical results showed that the SOC decreased by 7.21% and the simulation by 4.94% in terms of power consumption in a cycle. The power consumption variance was within a reasonable range, which further verifies the feasibility of the strategy.

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Section: Rule-based Energy Management Strategymentioning

confidence: 99%

Energy Management of Sowing Unit for Extended-Range Electric Tractor Based on Improved CD-CS Fuzzy Rules

Wang

Xing

et al. 2023

Agriculture

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“…Ê òîìó aeå ñòîèìîñòü ÊÝÓ çíà÷èòåëüíî âûøå èç-çà ñëîaeíîñòè êîíñòðóêöèè, êîòîðàÿ âêëþ÷àåò äîïîëíèòåëüíûå êîìïîíåíòû: ýëåêòðîäâèãàòåëü, ñèëîâîé èíâåðòîð, ãåíåðàòîð è íàêîïèòåëü ýíåðãèè. Ê ýòîìó âûâîäó ïðèõîäÿò òàêaeå è äðóãèå èññëåäîâàòåëè [3].…”

Section: ââåäåíèåunclassified

Stabilization of the load mode of the internal combustion engine of the tractor through the use of a hybrid power plant

Rakov¹,

Litvinov²

2020

Traktory i sel hozmashiny

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It is known that the main costs in the operation of agricultural machinery are associated with fuels, lubricants and spare parts. The attempts are made to improve the performance of the machinery by reducing operating costs. This happens due to the increasing competitive requirements of the final product. For example, during daily operation of the MTZ-82 tractor, the most widespread tractor in the Eurasian Economic Union, when delivering feed and driving a feeder for a year of operation, just the fuel costs will amount to approximately 20 % of its initial cost (300 thousand Russian rubles). In addition, to ensure the tractor is in a working condition, it will require spare parts and other consumables for another hundreds of thousands of rubles in Russian currency. The diesel engine used in tractors idles most of the time and, as a result, is underloaded. In peak loads, on the contrary, more power is required and, accordingly, it is necessary to create a sufficient energy reserve. This in turn inevitably leads to increased fuel consumption. Hence, there is a need to stabilize the load mode of the engine, reduce its operation in underloaded modes and at maximum loads. This problem can be solved in various ways. One of them is a combination of a diesel engine and an electromechanical transmission. Such power plants are usually called combined or hybrid. Among several typical structural schemes in agricultural machinery, hybrid power plants of the mild hybrid type and full hybrid type were most widely used. The presented methodology will allow to analyze the proposed schemes of a hybrid power plant, assess possible losses and calculate the required engine power, and ultimately determine a more rational scheme for the given operating conditions. The authors also presented the results of a comparative calculation of the required power of an internal combustion engine of hybrid power plants.

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“…Several scholars have delved into optimization-based and intelligent-based research for pure electric and hybrid electric tractors. LEE et al [12] optimized power distribution in parallel hybrid tractors using dynamic programming (DP) algorithms, yielding significant results. Meanwhile, Li et al [13] proposed an enhanced DP algorithm for pure electric tractors, demonstrating superior optimization effects across three load conditions, resulting in an 18% reduction in total energy consumption.…”

Section: Introductionmentioning

confidence: 99%

Energy Management Optimization and Validation of a Hydrogen Fuel Cell-Powered Agricultural Tractor Based on Hierarchical Dynamic Programming

Li,

Liu,

Wang

et al. 2024

IEEE Access

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In addressing challenges associated with the constrained enhancement of range performance in pure electric tractors, the difficulty in achieving genuinely eco-friendly agricultural machinery with hybrid powertrains, and the outdated approaches to energy optimization in hydrogen fuel cell tractors, a comprehensive methodology covering the entire spectrum of system design, optimization, and validation is presented. This method constructs an integrated electromechanical and hydraulic power bond graph model for an agricultural tractor, encompassing energy systems, drive systems, and lifting systems. It achieves rapid interaction between 20-sim software and Matlab/Simulink software through a script toolbox. In order to tackle the real-time applicability challenges of dynamic programming, a hierarchical dynamic programming is proposed. The dynamic programming strategy results serve as the upper-level output. At the lower layer, preprocessing of impact value variables is carried out to filter the input variables for the general regression neural network. This enables the real-time application of the dynamic programming algorithm and significantly reduces training time. Finally, a Matlab-HIL test platform is established, utilizing 20-sim, Matlab/Simulink, HIL cabinet, and PowerECU-57A controller as the core components for the test of modelin-the-loop and hardware-in-the-loop. The results demonstrate the correctness and superiority of the designed tractor simulation model and energy management strategy model compared to the power-following strategy. Specifically, in plowing conditions, the dynamic programming and hierarchical dynamic programming strategies exhibited reductions of 10.278% and 6.728%, respectively, in equivalent hydrogen consumption compared to power-following strategy. In transportation conditions, the reductions are 16.02% for dynamic programming strategy and 4.87% for hierarchical dynamic programming strategy, both relative to powerfollowing strategy. This study lays the theoretical groundwork for modeling dynamic systems of tractors and optimizing energy management.INDEX TERMS hydrogen fuel cell tractors, bond graph, energy management strategy, model-in-the-loop, hard-ware-in-the-loop.

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Rule-based power distribution in the power train of a parallel hybrid tractor for fuel savings

Cited by 23 publications

References 6 publications

Energy Management of Sowing Unit for Extended-Range Electric Tractor Based on Improved CD-CS Fuzzy Rules

Energy Management of Sowing Unit for Extended-Range Electric Tractor Based on Improved CD-CS Fuzzy Rules

Stabilization of the load mode of the internal combustion engine of the tractor through the use of a hybrid power plant

Energy Management Optimization and Validation of a Hydrogen Fuel Cell-Powered Agricultural Tractor Based on Hierarchical Dynamic Programming

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