This paper presents an energy management optimization system based on an adaptive functional state model of battery aging for internal combustion engine vehicles(ICEVs).First,the functional characteristics of batterie...This paper presents an energy management optimization system based on an adaptive functional state model of battery aging for internal combustion engine vehicles(ICEVs).First,the functional characteristics of batteries in ICEVs are investigated.Then,an adaptive functional state model is proposed to represent battery aging throughout the entire battery service life.A battery protection scheme is developed,including over-discharge and graded over-current protection to improve battery safety.A model-based energy management strategy is synthesized to comprehensively optimize fuel economy,battery life preservation,and vehicle performance.The performance of the proposed scheme was examined under comprehensive test scenarios based on field and bench tests.The results show that the proposed energy management algorithm can effectively improve fuel economy.展开更多
The diffusion of new energy vehicles(NEVs),such as battery electric vehicles(BEVs)and fuel cell vehicles(FCVs),is critical to the transportation sector's deep decarbonization.The cost of energy chains is an import...The diffusion of new energy vehicles(NEVs),such as battery electric vehicles(BEVs)and fuel cell vehicles(FCVs),is critical to the transportation sector's deep decarbonization.The cost of energy chains is an important factor in the diffusion of NEVs.Although researchers have addressed the technological learning effect of NEVs and the life cycle emissions associated with the diffusion of NEVs,little work has been conducted to analyze the life cycle costs of different energy chains associated with different NEVs in consideration of technological learning potential.Thus,relevant information on investment remains insufficient to promote the deployment of NEVs.This study proposes a systematic framework that includes various(competing or coordinated)energy chains of NEVs formed with different technologies of power generation and transmission,hydrogen production and transportation,power-to-liquid fuel,and fuel transportation.The levelized costs of three typical carbon-neutral energy chains are investigated using the life cycle cost model and considering the technological learning effect.Results show that the current well-to-pump levelized costs of the energy chains in China for BEVs,FCVs,and internal combustion engine vehicles(ICEVs)are approximately 3.60,4.31,and 2.21 yuan/GJ,respectively,and the well-to-wheel levelized costs are 4.50,6.15,and 7.51 yuan/GJ,respectively.These costs primarily include raw material costs and they vary greatly for BEVs and FCVs from resource and consumer costs.In consideration of the technological learning effect,the energy chains'well-to-wheel levelized costs are expected todecrease by 24.82%for BEVs,27.12%for FCVs,and 19.25%for ICEVs by 2060.This work also summarizes policy recommendations on developing energy chains to promote the diffusion of NEVs in China.展开更多
基金supported by National Natural Science Foundation of China(Grant No.52002209)Beijing Nova Program,and the State Key Laboratory of Automotive Safety and Energy(Grant No.KFY2210).
文摘This paper presents an energy management optimization system based on an adaptive functional state model of battery aging for internal combustion engine vehicles(ICEVs).First,the functional characteristics of batteries in ICEVs are investigated.Then,an adaptive functional state model is proposed to represent battery aging throughout the entire battery service life.A battery protection scheme is developed,including over-discharge and graded over-current protection to improve battery safety.A model-based energy management strategy is synthesized to comprehensively optimize fuel economy,battery life preservation,and vehicle performance.The performance of the proposed scheme was examined under comprehensive test scenarios based on field and bench tests.The results show that the proposed energy management algorithm can effectively improve fuel economy.
基金This work was supported by the National Natural Science Foundation of China(Grant Nos.72131007,7214006,and 72074077)Open access funding provided by International Institute for Applied Systems Analysis(IIASA).
文摘The diffusion of new energy vehicles(NEVs),such as battery electric vehicles(BEVs)and fuel cell vehicles(FCVs),is critical to the transportation sector's deep decarbonization.The cost of energy chains is an important factor in the diffusion of NEVs.Although researchers have addressed the technological learning effect of NEVs and the life cycle emissions associated with the diffusion of NEVs,little work has been conducted to analyze the life cycle costs of different energy chains associated with different NEVs in consideration of technological learning potential.Thus,relevant information on investment remains insufficient to promote the deployment of NEVs.This study proposes a systematic framework that includes various(competing or coordinated)energy chains of NEVs formed with different technologies of power generation and transmission,hydrogen production and transportation,power-to-liquid fuel,and fuel transportation.The levelized costs of three typical carbon-neutral energy chains are investigated using the life cycle cost model and considering the technological learning effect.Results show that the current well-to-pump levelized costs of the energy chains in China for BEVs,FCVs,and internal combustion engine vehicles(ICEVs)are approximately 3.60,4.31,and 2.21 yuan/GJ,respectively,and the well-to-wheel levelized costs are 4.50,6.15,and 7.51 yuan/GJ,respectively.These costs primarily include raw material costs and they vary greatly for BEVs and FCVs from resource and consumer costs.In consideration of the technological learning effect,the energy chains'well-to-wheel levelized costs are expected todecrease by 24.82%for BEVs,27.12%for FCVs,and 19.25%for ICEVs by 2060.This work also summarizes policy recommendations on developing energy chains to promote the diffusion of NEVs in China.