Research on Energy Management Strategy of Pure Electric Vacuum Vehicle Based on Fuzzy Control

Wang, Yujie; Lei, Yu; Zhang, Licheng; Zhong, Shengshi

doi:10.3389/fenrg.2022.935484

Cited by 2 publications

(3 citation statements)

References 18 publications

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“…Based on MATLAB 2019a/Simulink, we develop a simulation model for a hybrid electric vehicle system to explore the coupling characteristics and energy management strategies of multi-energy systems under complex operating conditions [38], as shown in Figure 5. The results from parameter matching are incorporated into the Powertrain Block set module, and the constructed model replaces the standard model framework.…”

Section: Establishment Of a Vehicle Energy Management Modelmentioning

confidence: 99%

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Research on Energy Hierarchical Management and Optimal Control of Compound Power Electric Vehicle

Zhang,

Tang,

Zhang

et al. 2024

Energies

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In response to the challenges posed by the low energy utilization of single-power pure electric vehicles and the limited lifespan of power batteries, this study focuses on the development of a compound power system. This study constructs a composite power system, analyzes the coupling characteristics of multiple systems, and investigates the energy management and optimal control mechanisms. Firstly, a power transmission scheme is designed for a hybrid electric vehicle. Then, a multi-state model is established to assess the electric vehicle’s performance under complex working conditions and explore how these conditions impact system coupling. Next, load power is redistributed using the Haar wavelet theory. The super capacitor is employed to stabilize chaotic and transient components in the required power, with low-frequency components serving as input variables for the controller. Further, power distribution is determined through the application of fuzzy logic theory. Input parameters include the system’s power requirements, power battery status, and super capacitor state of charge. The result is the output of a composite power supply distribution factor. To fully exploit the composite power supply’s potential and optimize the overall system performance, a global optimization control strategy using the dynamic programming algorithm is explored. The optimization objective is to minimize power loss within the composite power system, and the optimal control is calculated through interpolation using the interp function. Finally, a comparative simulation experiment is conducted under UDDS cycle conditions. The results show that the composite power system improved the battery discharge efficiency and reduced the number of discharge cycles and discharge current of the power battery. Under the cyclic working condition of 1369 s, the state of charge of the power battery in the hybrid power system decreases from 0.9 to 0.69, representing a 12.5% increase compared to the single power system. The peak current of the power battery in the hybrid power system decreases by approximately 20 A compared with that in the single power system. Based on dynamic programming optimization, the state of charge of the power battery decreases from 0.9 to 0.724. Compared with that of the single power system, the power consumption of the proposed system increases by 25%, that of the hybrid power fuzzy control system increases by 14.2%, and that of the vehicle decreases by 14.7% after dynamic programming optimization. The multimode energy shunt relationship is solved through efficient and reasonable energy management and optimization strategies. The performance and advantages of the composite energy storage system are fully utilized. This approach provides a new idea for the energy storage scheme of new energy vehicles.

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Section: Establishment Of a Vehicle Energy Management Modelmentioning

confidence: 99%

Section: Establishment Of a Vehicle Energy Management Modelmentioning

confidence: 99%

Research on Energy Hierarchical Management and Optimal Control of Compound Power Electric Vehicle

Zhang,

Tang,

Zhang

et al. 2024

Energies

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“…With the development of intelligent agriculture, a modern agricultural sowing environment is more and more urgent for intelligent agricultural machinery equipment such as an extended-range electric tractor, which has a range extender unit installed on the pure electric tractor infrastructure to extend the travel range and ensure the continuity of operation [1][2][3][4]. Currently, the main demand of extended-range electric tractors is for smalland medium-load operation.…”

Section: Introductionmentioning

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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Research on Energy Management Strategy of Pure Electric Vacuum Vehicle Based on Fuzzy Control

Cited by 2 publications

References 18 publications

Research on Energy Hierarchical Management and Optimal Control of Compound Power Electric Vehicle

Research on Energy Hierarchical Management and Optimal Control of Compound Power Electric Vehicle

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

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