SOC (State Of Charge) estimation based battery management is important for HEV (Hybrid Electric Vehicle) applications. There are many difficulties in SOC estimation of HEV NiMH (Nickel Metal Hydroxide) batteries, for example, gassing at charge, self discharge, hysteresis and relaxation of OCV (Open Circuit Voltage), memory effect during charge-discharge cycling, and so on. In this paper, a mode...

Hybrid, plug-in hybrid, and electric vehicles have enthusiastically embraced rechargeable Li-ion batteries as their primary/supplemental power source of choice. Because the state of charge (SoC) of a battery indicates available remaining energy, the battery management system of these vehicles must estimate the SoC accurately. To estimate the SoC of Li-ion batteries, we derive a normalized state...

The rapidly growing demand for energy storage has spurred the development of advanced Li-ion batteries. Physical-based modeling techniques have emerged as a powerful tool to assist battery technologies because advantages relating performances internal physical and (electro)chemical processes. In present paper, pseudo-two-dimensional (P2D) based model been developed batteries with NCA cathodes C...

This paper focuses on state of charge (SOC) estimation for the battery packs of electric vehicles (EVs). By modeling a battery based on the equivalent circuit model (ECM), the adaptive extended Kalman filter (AEKF) method can be applied to estimate the battery cell SOC. By adaptively setting different weighed coefficients, a battery pack SOC estimation algorithm is established based on the sing...

Battery maintainers are widely used in marine and ground vehicles whose batteries have cycles of operation involving long periods of non-active life. Durability of such batteries, without proper maintenance, does not exceed one year. Extension of the battery life-time requires very thorough monitoring and periodic, preferably automatic recharging to replenish lost charge due to battery selfdisc...

The fast charge battery control problem is characterized by the need to have a sufficiently detailed model that can capture both the charging process and the inevitable constraints that limit the rate of charging due to battery state of health requirements. Presently, it appears the minimal modeling requirements to address the charging problem in model based fashion are unknown. This work seeks...

Energy consumption is a major concern in context-aware smartphone sensing. This paper first studies mobile device-based battery modeling, which adopts the kinetic battery model (KiBaM), under the scope of battery non-linearities with respect to variant loads. Second, this paper models the energy consumption behavior of accelerometers analytically and then provides extensive simulation results a...