The effect of cycling on the state of health of the electric vehicle battery

This paper provides an analysis of the experimental results available for lithium ion battery degradation which has been used to create a model of the effect of the identified parameters on the ageing of an EV battery. The parameters affecting degradation are generally accepted to be; state of charge, depth of discharge, charging rate and battery temperature. Values for each of these parameters have been found for three versions of a typical daily cycling scenario; uncontrolled charging, delayed charging and V2G. A comparison is made of the expected overall degradation using four different charging rates and different charging patterns based on the model. A link is made between the charging patterns and the effect on the power flow at the transformer of a typical section of LV network using a ADMD profile. The analysis shows that delayed charging and V2G slow down the rate of battery degradation. However, fast charging appears to accelerate battery degradation. Delayed charging also helps avoid excessive evening loading and thus will help delay distribution network asset upgrading. Uncontrolled charging increases evening loading and V2G can reduce it. However, the EV then needs more power for charging and the charging after V2G needs to be managed if it is not to create another spike in demand at a later time.

[1]  Graeme Hill,et al.  Monitoring and predicting charging behaviour for electric vehicles , 2012, 2012 IEEE Intelligent Vehicles Symposium.

[2]  Dirk Uwe Sauer,et al.  Concept of a Battery Aging Model for Lithium-Ion Batteries Considering the Lifetime Dependency on the Operation Strategy , 2009 .

[3]  Graeme Hill,et al.  Analysis of Electric Vehicle Driver Charging Behaviour and Use of Charging Infrastructure , 2012 .

[4]  J. Apt,et al.  Lithium-ion battery cell degradation resulting from realistic vehicle and vehicle-to-grid utilization , 2010 .

[5]  Matthieu Dubarry,et al.  Evaluation of commercial lithium-ion cells based on composite positive electrode for plug-in hybrid electric vehicle applications. Part II. Degradation mechanism under 2 C cycle aging , 2011 .

[6]  G. A. Putrus,et al.  Impact of electric vehicles on power distribution networks , 2009, 2009 IEEE Vehicle Power and Propulsion Conference.

[7]  Dirk Uwe Sauer,et al.  Optimizing vehicle-to-grid charging strategies using genetic algorithms under the consideration of battery aging , 2011, 2011 IEEE Vehicle Power and Propulsion Conference.

[8]  Charles Abraham,et al.  Mainstream consumers driving plug-in battery-electric and plug-in hybrid electric cars: A qualitative analysis of responses and evaluations , 2012 .

[9]  Shinji Inazawa,et al.  Development of long life lithium ion battery for power storage , 2001 .

[10]  Gan Ning,et al.  Cycle Life Modeling of Lithium-Ion Batteries , 2004 .

[11]  Olivier Tremblay,et al.  Experimental validation of a battery dynamic model for EV applications , 2009 .

[12]  Dirk Uwe Sauer,et al.  Influence of plug-in hybrid electric vehicle charging strategies on charging and battery degradation costs , 2012 .

[13]  Alan Millner,et al.  Modeling Lithium Ion battery degradation in electric vehicles , 2010, 2010 IEEE Conference on Innovative Technologies for an Efficient and Reliable Electricity Supply.

[14]  Graeme Hill,et al.  Understanding Electric Vehicles Usage and the Role of ITS: The North East England Electric Vehicle and Infrastructure Trials , 2012 .

[15]  Zhiwei Gao,et al.  Development of a decentralized smart charge controller for electric vehicles , 2014 .

[16]  Suzanna Long,et al.  Barriers to widespread adoption of electric vehicles: An analysis of consumer attitudes and perceptions , 2012 .