The remaining available energy is a critically priori information for the energy management and the remaining driving range prediction, which is also an urgent problem needed to be solved for electric vehicles.
What is battery remaining available energy prediction?
The remaining available energy is a critically priori information for the energy management and the remaining driving range prediction, which is also an urgent problem needed to be solved for electric vehicles. An effective and reliable approach for battery remaining available energy prediction is proposed and verified. 1.
Is battery remaining available energy a critical priori information?
Conclusions The remaining available energy is a critically priori information for the energy management and the remaining driving range prediction, which is also an urgent problem needed to be solved for electric vehicles. An effective and reliable approach for battery remaining available energy prediction is proposed and verified.
Can lithium-ion batteries predict remaining driving range based on electrothermal effect?
Accurate remaining available energy (E RAE) prediction of lithium-ion batteries is still a challenging issue for electric vehicles, which is crucial for the prediction of remaining driving range. An approach for battery E RAE prediction is proposed considering the electrothermal effect and energy-conversion-efficiency.
How accurate is the RUL of energy storage batteries?
According to the low prediction accuracy of the RUL of energy storage batteries, this paper proposes a prediction model of the RUL of energy storage batteries based on multimodel integration. The inputs are first divided into three groups, which are maximum, average, and minimum groups to validate the input characteristics.
Can lithium-ion battery remaining discharge energy prediction be used in electric vehicles?
A highly accurate predictive-adaptive method for lithium-ion battery remaining discharge energy prediction in electric vehicle applications Appl. Energy, 149 ( 2015), pp. 297 - 314, 10.1016/j.apenergy.2015.03.110 Y.Z. Zhang, H.W. He, R. Xiong A data-driven based state of energy estimator of lithium-ion batteries used to supply electric vehicles
Is there an adaptive remaining energy prediction approach for lithium-ion batteries?
An adaptive remaining energy prediction approach for lithium-ion batteries in electric vehicles J. Power Sources, 305 ( 2016), pp. 80 - 88, 10.1016/j.jpowsour.2015.11.087 Probability based remaining capacity estimation using data-driven and neural network model J. Power Sources, 315 ( 2016), pp. 199 - 208, 10.1016/j.jpowsour.2016.03.054