Energy Management Strategy of a Novel Electric Dual-Motor Transmission for Heavy Commercial Vehicles Based on APSO Algorithm

Liang, Jiajia; Xu, Xiangyang; Dong, Peng; Feng, Tao; Guo, Wei; Wang, Shuhan

doi:10.3390/su14031163

Cited by 4 publications

(2 citation statements)

References 30 publications

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“…This section applies the OBH algorithm to MCL and replaces the general algorithm in Section 5.2 with several excellent algorithms to exploit the potential of the OBH algorithm further, such as adaptive particle swarm optimization (APSO) [44], differential evolution (DE) [45], GWO, and PSO. In each group of experiments, the number of nodes remained unchanged, with a total of 200, and the number of anchor nodes gradually increased from 5 to 30.…”

Section: Application In Monte Carlo Localizationmentioning

confidence: 99%

An Opposition-Based Learning Black Hole Algorithm for Localization of Mobile Sensor Network

Zheng

Pan

et al. 2023

Sensors

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The mobile node location method can find unknown nodes in real time and capture the movement trajectory of unknown nodes in time, which has attracted more and more attention from researchers. Due to their advantages of simplicity and efficiency, intelligent optimization algorithms are receiving increasing attention. Compared with other algorithms, the black hole algorithm has fewer parameters and a simple structure, which is more suitable for node location in wireless sensor networks. To address the problems of weak merit-seeking ability and slow convergence of the black hole algorithm, this paper proposed an opposition-based learning black hole (OBH) algorithm and utilized it to improve the accuracy of the mobile wireless sensor network (MWSN) localization. To verify the performance of the proposed algorithm, this paper tests it on the CEC2013 test function set. The results indicate that among the several algorithms tested, the OBH algorithm performed the best. In this paper, several optimization algorithms are applied to the Monte Carlo localization algorithm, and the experimental results show that the OBH algorithm can achieve the best optimization effect in advance.

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Section: Application In Monte Carlo Localizationmentioning

confidence: 99%

An Opposition-Based Learning Black Hole Algorithm for Localization of Mobile Sensor Network

Zheng

Pan

et al. 2023

Sensors

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“…An increasing number of studies have provided deep insight into the new energy vehicle technologies to improve energy efficiency and reduce the impact on the environment. Energy management and optimization strategies that can increase the driving range and reduce the emissions and fuel consumption have been put forward [12][13][14][15][16]. Moreover, energy conversion efficiencies and fuel saving effects to different extents can be demonstrated by employing different transmission topologies [17][18][19].…”

Section: Literature Reviewmentioning

confidence: 99%

Life Cycle Assessment of Energy Consumption and CO2 Emission from HEV, PHEV and BEV for China in the Past, Present and Future

Wang

Song

et al. 2022

Energies

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In order to fulfill the commitment of China to achieve carbon peak by 2030 and carbon neutrality by 2060, all industries have been taking their respective carbon reduction actions. The transportation industry accounts for 11% of CO2 emission of the whole society, and its energy conservation and carbon reduction benefit is of great significance to the national carbon reduction process. New energy vehicles are undoubtedly one of the most important means of carbon emission reduction in the transportation sector. However, electric vehicles still have CO2 emissions, as the fossil fuel use comes from upstream power. To systematically and comprehensively evaluate the CO2 emissions of HEV, PHEV and BEV in the whole process, this study introduces the life-cycle method to research on the past and current situations, and predict future scenarios for ICEV and EV light-duty vehicles at the national and regional levels, by deeply analyzing the generation mix and generating efficiency from the WTT stage, and fuel economy from the TTW stage. The study shows that compared with ICEV, HEV and PHEV could reduce around 30% of CO2 emissions. Currently, BEV could reduce 37% of CO2 emission in the region where the proportion of coal-fired power is high, and 90% of CO2 emission in the region where the proportion of hydro power is high. This study discusses the impact of the proportion of renewable energy application on the carbon emissions from electric vehicles, analyzes the environmental benefits of promoting electric vehicles in different regions, and lays a foundation for the promotion strategy of electric vehicles for different regions in the future.

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Optimal sizing and energy management of a novel dual-motor powertrain for electric vehicles

Yang

Zhang

et al. 2023

Energy

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Energy Management Strategy of a Novel Electric Dual-Motor Transmission for Heavy Commercial Vehicles Based on APSO Algorithm

Cited by 4 publications

References 30 publications

An Opposition-Based Learning Black Hole Algorithm for Localization of Mobile Sensor Network

An Opposition-Based Learning Black Hole Algorithm for Localization of Mobile Sensor Network

Life Cycle Assessment of Energy Consumption and CO2 Emission from HEV, PHEV and BEV for China in the Past, Present and Future

Optimal sizing and energy management of a novel dual-motor powertrain for electric vehicles

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