Fuzzy energy management strategy for hybrid electric vehicles on battery state-of-charge estimation by particle filter

Abstract The battery/ultracapacitor hybrid power supply system can solve the problems of high cost and short life of a single power system, and the energy management of hybrid power system has become a vital issue in the field of electric vehicles. In this paper, a fuzzy energy management strategy o...
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Autor*in:	Na Feng [verfasserIn] Tiehua Ma [verfasserIn] Changxin Chen [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2022

Schlagwörter:	Hybrid electric vehicle (HEV) SOC estimation Energy management strategy Fuzzy controller Particle filter algorithm

Übergeordnetes Werk:	In: SN Applied Sciences - Springer, 2021, 4(2022), 10, Seite 11
Übergeordnetes Werk:	volume:4 ; year:2022 ; number:10 ; pages:11

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc Journal toc

DOI / URN:	10.1007/s42452-022-05131-8

Katalog-ID:	DOAJ085105910

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520			\|a Abstract The battery/ultracapacitor hybrid power supply system can solve the problems of high cost and short life of a single power system, and the energy management of hybrid power system has become a vital issue in the field of electric vehicles. In this paper, a fuzzy energy management strategy on the state-of-charge (SOC) estimation of power battery is proposed. Particle filter (PF) algorithm is used to estimate SOC of power battery, then estimated result is regarded as the input variable of fuzzy energy management controller, and the energy distribution result is obtained after fuzzy logic operation. The simulation results show that the SOC estimation result of the PF algorithm is closer to the actual value of power battery SOC. When the SOC estimation result of PF is embedded into the fuzzy controller for joint simulation, it is found that the charge and discharge current, and SOC consumption of the power battery are reduced, which shows the algorithm’s effectiveness. It also provides a specific reference value for the further study of the power supply control strategy of hybrid electric vehicles.
650		4	\|a Hybrid electric vehicle (HEV)
650		4	\|a SOC estimation
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allfields	10.1007/s42452-022-05131-8 doi (DE-627)DOAJ085105910 (DE-599)DOAJee93134afe4d43bb85aa74c7bfaf4e5e DE-627 ger DE-627 rakwb eng Na Feng verfasserin aut Fuzzy energy management strategy for hybrid electric vehicles on battery state-of-charge estimation by particle filter 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The battery/ultracapacitor hybrid power supply system can solve the problems of high cost and short life of a single power system, and the energy management of hybrid power system has become a vital issue in the field of electric vehicles. In this paper, a fuzzy energy management strategy on the state-of-charge (SOC) estimation of power battery is proposed. Particle filter (PF) algorithm is used to estimate SOC of power battery, then estimated result is regarded as the input variable of fuzzy energy management controller, and the energy distribution result is obtained after fuzzy logic operation. The simulation results show that the SOC estimation result of the PF algorithm is closer to the actual value of power battery SOC. When the SOC estimation result of PF is embedded into the fuzzy controller for joint simulation, it is found that the charge and discharge current, and SOC consumption of the power battery are reduced, which shows the algorithm’s effectiveness. It also provides a specific reference value for the further study of the power supply control strategy of hybrid electric vehicles. Hybrid electric vehicle (HEV) SOC estimation Energy management strategy Fuzzy controller Particle filter algorithm Science Q Technology T Tiehua Ma verfasserin aut Changxin Chen verfasserin aut In SN Applied Sciences Springer, 2021 4(2022), 10, Seite 11 (DE-627)103761139X 25233971 nnns volume:4 year:2022 number:10 pages:11 https://doi.org/10.1007/s42452-022-05131-8 kostenfrei https://doaj.org/article/ee93134afe4d43bb85aa74c7bfaf4e5e kostenfrei https://doi.org/10.1007/s42452-022-05131-8 kostenfrei https://doaj.org/toc/2523-3963 Journal toc kostenfrei https://doaj.org/toc/2523-3971 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_90 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 4 2022 10 11
spelling	10.1007/s42452-022-05131-8 doi (DE-627)DOAJ085105910 (DE-599)DOAJee93134afe4d43bb85aa74c7bfaf4e5e DE-627 ger DE-627 rakwb eng Na Feng verfasserin aut Fuzzy energy management strategy for hybrid electric vehicles on battery state-of-charge estimation by particle filter 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The battery/ultracapacitor hybrid power supply system can solve the problems of high cost and short life of a single power system, and the energy management of hybrid power system has become a vital issue in the field of electric vehicles. In this paper, a fuzzy energy management strategy on the state-of-charge (SOC) estimation of power battery is proposed. Particle filter (PF) algorithm is used to estimate SOC of power battery, then estimated result is regarded as the input variable of fuzzy energy management controller, and the energy distribution result is obtained after fuzzy logic operation. The simulation results show that the SOC estimation result of the PF algorithm is closer to the actual value of power battery SOC. When the SOC estimation result of PF is embedded into the fuzzy controller for joint simulation, it is found that the charge and discharge current, and SOC consumption of the power battery are reduced, which shows the algorithm’s effectiveness. It also provides a specific reference value for the further study of the power supply control strategy of hybrid electric vehicles. Hybrid electric vehicle (HEV) SOC estimation Energy management strategy Fuzzy controller Particle filter algorithm Science Q Technology T Tiehua Ma verfasserin aut Changxin Chen verfasserin aut In SN Applied Sciences Springer, 2021 4(2022), 10, Seite 11 (DE-627)103761139X 25233971 nnns volume:4 year:2022 number:10 pages:11 https://doi.org/10.1007/s42452-022-05131-8 kostenfrei https://doaj.org/article/ee93134afe4d43bb85aa74c7bfaf4e5e kostenfrei https://doi.org/10.1007/s42452-022-05131-8 kostenfrei https://doaj.org/toc/2523-3963 Journal toc kostenfrei https://doaj.org/toc/2523-3971 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_90 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 4 2022 10 11
allfields_unstemmed	10.1007/s42452-022-05131-8 doi (DE-627)DOAJ085105910 (DE-599)DOAJee93134afe4d43bb85aa74c7bfaf4e5e DE-627 ger DE-627 rakwb eng Na Feng verfasserin aut Fuzzy energy management strategy for hybrid electric vehicles on battery state-of-charge estimation by particle filter 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The battery/ultracapacitor hybrid power supply system can solve the problems of high cost and short life of a single power system, and the energy management of hybrid power system has become a vital issue in the field of electric vehicles. In this paper, a fuzzy energy management strategy on the state-of-charge (SOC) estimation of power battery is proposed. Particle filter (PF) algorithm is used to estimate SOC of power battery, then estimated result is regarded as the input variable of fuzzy energy management controller, and the energy distribution result is obtained after fuzzy logic operation. The simulation results show that the SOC estimation result of the PF algorithm is closer to the actual value of power battery SOC. When the SOC estimation result of PF is embedded into the fuzzy controller for joint simulation, it is found that the charge and discharge current, and SOC consumption of the power battery are reduced, which shows the algorithm’s effectiveness. It also provides a specific reference value for the further study of the power supply control strategy of hybrid electric vehicles. Hybrid electric vehicle (HEV) SOC estimation Energy management strategy Fuzzy controller Particle filter algorithm Science Q Technology T Tiehua Ma verfasserin aut Changxin Chen verfasserin aut In SN Applied Sciences Springer, 2021 4(2022), 10, Seite 11 (DE-627)103761139X 25233971 nnns volume:4 year:2022 number:10 pages:11 https://doi.org/10.1007/s42452-022-05131-8 kostenfrei https://doaj.org/article/ee93134afe4d43bb85aa74c7bfaf4e5e kostenfrei https://doi.org/10.1007/s42452-022-05131-8 kostenfrei https://doaj.org/toc/2523-3963 Journal toc kostenfrei https://doaj.org/toc/2523-3971 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_90 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 4 2022 10 11
allfieldsGer	10.1007/s42452-022-05131-8 doi (DE-627)DOAJ085105910 (DE-599)DOAJee93134afe4d43bb85aa74c7bfaf4e5e DE-627 ger DE-627 rakwb eng Na Feng verfasserin aut Fuzzy energy management strategy for hybrid electric vehicles on battery state-of-charge estimation by particle filter 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The battery/ultracapacitor hybrid power supply system can solve the problems of high cost and short life of a single power system, and the energy management of hybrid power system has become a vital issue in the field of electric vehicles. In this paper, a fuzzy energy management strategy on the state-of-charge (SOC) estimation of power battery is proposed. Particle filter (PF) algorithm is used to estimate SOC of power battery, then estimated result is regarded as the input variable of fuzzy energy management controller, and the energy distribution result is obtained after fuzzy logic operation. The simulation results show that the SOC estimation result of the PF algorithm is closer to the actual value of power battery SOC. When the SOC estimation result of PF is embedded into the fuzzy controller for joint simulation, it is found that the charge and discharge current, and SOC consumption of the power battery are reduced, which shows the algorithm’s effectiveness. It also provides a specific reference value for the further study of the power supply control strategy of hybrid electric vehicles. Hybrid electric vehicle (HEV) SOC estimation Energy management strategy Fuzzy controller Particle filter algorithm Science Q Technology T Tiehua Ma verfasserin aut Changxin Chen verfasserin aut In SN Applied Sciences Springer, 2021 4(2022), 10, Seite 11 (DE-627)103761139X 25233971 nnns volume:4 year:2022 number:10 pages:11 https://doi.org/10.1007/s42452-022-05131-8 kostenfrei https://doaj.org/article/ee93134afe4d43bb85aa74c7bfaf4e5e kostenfrei https://doi.org/10.1007/s42452-022-05131-8 kostenfrei https://doaj.org/toc/2523-3963 Journal toc kostenfrei https://doaj.org/toc/2523-3971 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_90 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 4 2022 10 11
allfieldsSound	10.1007/s42452-022-05131-8 doi (DE-627)DOAJ085105910 (DE-599)DOAJee93134afe4d43bb85aa74c7bfaf4e5e DE-627 ger DE-627 rakwb eng Na Feng verfasserin aut Fuzzy energy management strategy for hybrid electric vehicles on battery state-of-charge estimation by particle filter 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The battery/ultracapacitor hybrid power supply system can solve the problems of high cost and short life of a single power system, and the energy management of hybrid power system has become a vital issue in the field of electric vehicles. In this paper, a fuzzy energy management strategy on the state-of-charge (SOC) estimation of power battery is proposed. Particle filter (PF) algorithm is used to estimate SOC of power battery, then estimated result is regarded as the input variable of fuzzy energy management controller, and the energy distribution result is obtained after fuzzy logic operation. The simulation results show that the SOC estimation result of the PF algorithm is closer to the actual value of power battery SOC. When the SOC estimation result of PF is embedded into the fuzzy controller for joint simulation, it is found that the charge and discharge current, and SOC consumption of the power battery are reduced, which shows the algorithm’s effectiveness. It also provides a specific reference value for the further study of the power supply control strategy of hybrid electric vehicles. Hybrid electric vehicle (HEV) SOC estimation Energy management strategy Fuzzy controller Particle filter algorithm Science Q Technology T Tiehua Ma verfasserin aut Changxin Chen verfasserin aut In SN Applied Sciences Springer, 2021 4(2022), 10, Seite 11 (DE-627)103761139X 25233971 nnns volume:4 year:2022 number:10 pages:11 https://doi.org/10.1007/s42452-022-05131-8 kostenfrei https://doaj.org/article/ee93134afe4d43bb85aa74c7bfaf4e5e kostenfrei https://doi.org/10.1007/s42452-022-05131-8 kostenfrei https://doaj.org/toc/2523-3963 Journal toc kostenfrei https://doaj.org/toc/2523-3971 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_90 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 4 2022 10 11
language	English
source	In SN Applied Sciences 4(2022), 10, Seite 11 volume:4 year:2022 number:10 pages:11
sourceStr	In SN Applied Sciences 4(2022), 10, Seite 11 volume:4 year:2022 number:10 pages:11
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Hybrid electric vehicle (HEV) SOC estimation Energy management strategy Fuzzy controller Particle filter algorithm Science Q Technology T
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container_title	SN Applied Sciences
authorswithroles_txt_mv	Na Feng @@aut@@ Tiehua Ma @@aut@@ Changxin Chen @@aut@@
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In this paper, a fuzzy energy management strategy on the state-of-charge (SOC) estimation of power battery is proposed. Particle filter (PF) algorithm is used to estimate SOC of power battery, then estimated result is regarded as the input variable of fuzzy energy management controller, and the energy distribution result is obtained after fuzzy logic operation. The simulation results show that the SOC estimation result of the PF algorithm is closer to the actual value of power battery SOC. When the SOC estimation result of PF is embedded into the fuzzy controller for joint simulation, it is found that the charge and discharge current, and SOC consumption of the power battery are reduced, which shows the algorithm’s effectiveness. 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author	Na Feng
spellingShingle	Na Feng misc Hybrid electric vehicle (HEV) misc SOC estimation misc Energy management strategy misc Fuzzy controller misc Particle filter algorithm misc Science misc Q misc Technology misc T Fuzzy energy management strategy for hybrid electric vehicles on battery state-of-charge estimation by particle filter
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topic_title	Fuzzy energy management strategy for hybrid electric vehicles on battery state-of-charge estimation by particle filter Hybrid electric vehicle (HEV) SOC estimation Energy management strategy Fuzzy controller Particle filter algorithm
topic	misc Hybrid electric vehicle (HEV) misc SOC estimation misc Energy management strategy misc Fuzzy controller misc Particle filter algorithm misc Science misc Q misc Technology misc T
topic_unstemmed	misc Hybrid electric vehicle (HEV) misc SOC estimation misc Energy management strategy misc Fuzzy controller misc Particle filter algorithm misc Science misc Q misc Technology misc T
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title	Fuzzy energy management strategy for hybrid electric vehicles on battery state-of-charge estimation by particle filter
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title_full	Fuzzy energy management strategy for hybrid electric vehicles on battery state-of-charge estimation by particle filter
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title_sort	fuzzy energy management strategy for hybrid electric vehicles on battery state-of-charge estimation by particle filter
title_auth	Fuzzy energy management strategy for hybrid electric vehicles on battery state-of-charge estimation by particle filter
abstract	Abstract The battery/ultracapacitor hybrid power supply system can solve the problems of high cost and short life of a single power system, and the energy management of hybrid power system has become a vital issue in the field of electric vehicles. In this paper, a fuzzy energy management strategy on the state-of-charge (SOC) estimation of power battery is proposed. Particle filter (PF) algorithm is used to estimate SOC of power battery, then estimated result is regarded as the input variable of fuzzy energy management controller, and the energy distribution result is obtained after fuzzy logic operation. The simulation results show that the SOC estimation result of the PF algorithm is closer to the actual value of power battery SOC. When the SOC estimation result of PF is embedded into the fuzzy controller for joint simulation, it is found that the charge and discharge current, and SOC consumption of the power battery are reduced, which shows the algorithm’s effectiveness. It also provides a specific reference value for the further study of the power supply control strategy of hybrid electric vehicles.
abstractGer	Abstract The battery/ultracapacitor hybrid power supply system can solve the problems of high cost and short life of a single power system, and the energy management of hybrid power system has become a vital issue in the field of electric vehicles. In this paper, a fuzzy energy management strategy on the state-of-charge (SOC) estimation of power battery is proposed. Particle filter (PF) algorithm is used to estimate SOC of power battery, then estimated result is regarded as the input variable of fuzzy energy management controller, and the energy distribution result is obtained after fuzzy logic operation. The simulation results show that the SOC estimation result of the PF algorithm is closer to the actual value of power battery SOC. When the SOC estimation result of PF is embedded into the fuzzy controller for joint simulation, it is found that the charge and discharge current, and SOC consumption of the power battery are reduced, which shows the algorithm’s effectiveness. It also provides a specific reference value for the further study of the power supply control strategy of hybrid electric vehicles.
abstract_unstemmed	Abstract The battery/ultracapacitor hybrid power supply system can solve the problems of high cost and short life of a single power system, and the energy management of hybrid power system has become a vital issue in the field of electric vehicles. In this paper, a fuzzy energy management strategy on the state-of-charge (SOC) estimation of power battery is proposed. Particle filter (PF) algorithm is used to estimate SOC of power battery, then estimated result is regarded as the input variable of fuzzy energy management controller, and the energy distribution result is obtained after fuzzy logic operation. The simulation results show that the SOC estimation result of the PF algorithm is closer to the actual value of power battery SOC. When the SOC estimation result of PF is embedded into the fuzzy controller for joint simulation, it is found that the charge and discharge current, and SOC consumption of the power battery are reduced, which shows the algorithm’s effectiveness. It also provides a specific reference value for the further study of the power supply control strategy of hybrid electric vehicles.
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title_short	Fuzzy energy management strategy for hybrid electric vehicles on battery state-of-charge estimation by particle filter
url	https://doi.org/10.1007/s42452-022-05131-8 https://doaj.org/article/ee93134afe4d43bb85aa74c7bfaf4e5e https://doaj.org/toc/2523-3963 https://doaj.org/toc/2523-3971
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