Influence of Battery/Ultracapacitor Energy-Storage Sizing on Battery Lifetime in a Fuel Cell Hybrid Electric Vehicle
By Erik Schaltz, Alireza Khaligh, Peter Omand Rasmussen. IEEE Transactions on Vehicular Technology, 2009
337 citations recorded by the source corpus.
Subfields: Automotive Engineering, Electronic, Optical and Magnetic Materials
View Paper: https://www.semanticscholar.org/paper/74b563213b856f37588b64386e284706c0076d99
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Automotive Engineering
- Junyi Shen
- Serkan Dusmez
- Alireza Khaligh
- Seungmin Jeong
- Young Jae Jang
- Dongsuk Kum
- Rebecca Carter
- Andrew J. Cruden
In Electronic, Optical and Magnetic Materials
- Seungmin Jeong
- Young Jae Jang
- Dongsuk Kum
- Rebecca Carter
- Andrew J. Cruden
- Bernard Davat
- Peter J. Hall
Citations in the corpus
- Optimizing for Efficiency or Battery Life in a Battery/Supercapacitor Electric Vehicle (2012, background): “The rates of lead–acid battery aging may be decreased by factors including depth of discharge [14], high discharge currents [15], and high operating temperatures [15].”
- Energy Management of a Fuel Cell/Supercapacitor/Battery Power Source for Electric Vehicular Applications (2011, background): “The authors in [2], [3], and [23] have proposed an EMS in an”
- Economic Analysis of the Dynamic Charging Electric Vehicle (2015, methodology): “This model is called fatigue model, which is one of the cycle counting approaches [30], [33].”
- Optimization of Sizing and Battery Cycle Life in Battery/Ultracapacitor Hybrid Energy Storage Systems for Electric Vehicle Applications (2014, background): “Furthermore, the influence of battery/UC sizing on HESS efficiency and battery cycle life extension has been discussed in [12]–[14].”
- Optimal Bidding Strategy of Battery Storage in Power Markets Considering Performance-Based Regulation and Battery Cycle Life (2016, methodology): “In [20], battery lifetime is calculated to assess the battery and ultracapacitor ratings in electric vehicles.”
- Energy Management of Fuel Cell/Battery/Supercapacitor Hybrid Power Sources Using Model Predictive Control (2014, neutral): “They are wavelet transform [9], [10], fuzzy logic control [10], [16], load power sharing [11], supervisory control [12], sliding mode control [13], proportional integral control [4], [14], optimal control [15], and flatness control [16].”