Research on an Improved Rule-Based Energy Management Strategy Enlightened by the DP Optimization Results

Shi, Dapai; Guo, Junjie; Liu, Kangjie; Cai, Qingling; Wang, Zhenghong; Qu, Xudong

doi:10.3390/su151310472

Cited by 3 publications

(1 citation statement)

References 31 publications

(35 reference statements)

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“…Generally, global optimization strategies, such as dynamic programming (DP), require the complete a priori knowledge of the work cycle, and thus cannot be implemented in real time. However, since they can reach a global optimization, they are a used as benchmarks for the other strategies or as a tool to determine rules to be used in RBSs [102]. Apart from DP, other widely adopted global optimization algorithms are genetic algorithm, game theory, and stochastic dynamic programming [103][104][105].…”

Section: Control Strategies and Energy Managementmentioning

confidence: 99%

Trends and Future Perspective of Electrification in Agricultural Tractor-Implement Applications

Mocera,

Somà,

Martelli

et al. 2023

Energies

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The worldwide growing demand for food is pushing the agricultural field towards new innovative solutions to increase the efficiency and productivity of cultivations. In this direction, agricultural mechanization plays a crucial role, and tractors are among the most important actors. Agricultural tractors are machines designed to push/pull special instruments usually referred to as implements, to which they may transfer power by means of a mechanical power take-off (PTO) or via hydraulic connections, thanks to the availability of pressurized oil. The tractor can be seen as a mobile power station: the more efficiently it provides power to external implements or to the ground in terms of tractive effort, the higher will be the efficiency and productivity of a certain task. However, the growing demand for greener and sustainable work machines is pushing towards new concepts of tractor powertrains with the goal of reducing, as much as possible, the amount of pollutants and GHG emissions per unit of work. In this paper, the authors will propose a review of the current trends towards electrification of agricultural tractors. Electrification can help in making vehicles more efficient and opening a new scenario for work optimization. Moreover, electrification is also involving the implements attached to the tractor and responsible for actually performing a wide variety of field tasks. However, tractor electrification requires proper attention due to the impact of high power electric systems on the vehicle configuration. For this reason, a proper level of hybridization should be considered. In this paper, a new classification method will be proposed, considering the electrification level in terms of power and as a function of the installed electric energy storage. This definition will be applied to classify the current state of the art of electric and hybrid agricultural tractors, investigating current trends in the scientific community and among industrial manufacturers with a look to the new upcoming technologies.

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Section: Control Strategies and Energy Managementmentioning

confidence: 99%

Trends and Future Perspective of Electrification in Agricultural Tractor-Implement Applications

Mocera,

Somà,

Martelli

et al. 2023

Energies

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Integrated Optimization of Component Parameters and Energy Management Strategies for A Series–Parallel Hybrid Electric Vehicle

Fu,

Fan,

Lei

et al. 2024

Automot. Innov.

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Research on Plug-in Hybrid Electric Vehicle (PHEV) Energy Management Strategy with Dynamic Planning Considering Engine Start/Stop

Chen,

Wang,

Xie

et al. 2024

WEVJ

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The key to improving the fuel economy of plug-in hybrid electric vehicles (PHEVs) lies in the energy management strategy (EMS). Existing EMS often neglects engine operating conditions, leading to frequent start–stop events, which affect fuel economy and engine lifespan. This paper proposes an Integrated Engine Start–Stop Dynamic Programming (IESS-DP) energy management strategy, aiming to optimize energy consumption. An enhanced rule-based strategy is designed for the engine’s operating conditions, significantly reducing fuel consumption during idling through engine start–stop control. Furthermore, the IESS-DP energy management strategy is designed. This strategy comprehensively considers engine start–stop control states and introduces weighting coefficients to balance fuel consumption and engine start–stop costs. Precise control of energy flow is achieved through a global optimization framework to improve fuel economy. Simulation results show that under the World Light Vehicle Test Cycle (WLTC), the IESS-DP EMS achieves a fuel consumption of 3.36 L/100 km. This represents a reduction of 6.15% compared to the traditional DP strategy and 5.35% compared to the deep reinforcement learning-based EMS combined with engine start–stop (DDRL/SS) strategy. Additionally, the number of engine start–stop events is reduced by 43% compared to the DP strategy and 16% compared to the DDRL/SS strategy.

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Research on an Improved Rule-Based Energy Management Strategy Enlightened by the DP Optimization Results

Cited by 3 publications

References 31 publications

Trends and Future Perspective of Electrification in Agricultural Tractor-Implement Applications

Trends and Future Perspective of Electrification in Agricultural Tractor-Implement Applications

Integrated Optimization of Component Parameters and Energy Management Strategies for A Series–Parallel Hybrid Electric Vehicle

Research on Plug-in Hybrid Electric Vehicle (PHEV) Energy Management Strategy with Dynamic Planning Considering Engine Start/Stop

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