Optimal State-of-Charge Value for Charge-Sustaining Mode of Plug-In Hybrid Electric Vehicles

Abstract

For plug-in hybrid electric vehicles or extended range electric vehicles, battery stored energy often cannot fully meet the travel needs, and the battery needs to stay in a charge-sustaining mode to allow for backup sources such as gasoline or diesel to power the vehicle. It is crucial to identify the optimal stateof-charge (SOC) value for the battery to maintain this charge-sustaining mode since this SOC has significant impact to battery degradation. In existing studies, Just-in-Time control proposes that this SOC should be maintained at 55% but without theoretical justification. With the help of a battery degradation model based on solid electrolyte interphase growth, this paper develops a method to decide the optimal SOC value for charge-sustaining mode. Following the principle of superposition, degradation during the battery discharging process is divided as a fixed degradation caused by the drop of SOC from maximum to minimum values during charge-depleting mode, and a dynamic degradation caused by the oscillation at the charge-sustaining SOC value. Then this oscillation-caused degradation is further modeled and minimized through the investigation of the side reaction current density. The optimal SOC value obtained will be the SOC at which the side reaction current density has the slowest changing rate. This SOC value indeed relies on battery parameters, charging/discharging current and ambient temperature, and a case study shows that the best range of SOC value is 36%~38% for a 1.8Ah SONY 18650 cell. An average SOC of 37% is therefore recommended for charge-sustaining mode considering the possible errors in SOC estimation. INDEX TERMS Plug-in hybrid electric vehicle, state-of-charge, charge-sustaining, solid electrolyte interphase

Battery Reliability Assessment in Electric Vehicles: A State-of-the-Art

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Comparative Analysis of Hybrid Electric Architectures for Specialized Agricultural Tractors

“…From the system point of view, this component and its power flow needs to have the highest level of attention due to the time required to refill this energy reservoir. Thus, looking at Figure 12 the energy management strategy adopted for all the HET architectures can be described as follows (see Gao et al [28] and Zhang and Zhang [29]):…”

An improved adaptive spherical unscented Kalman filtering method for the accurate state‐of‐charge estimation of lithium‐ion batteries

“…The SOC can reflect the remaining capacity of the battery, and the battery usage strategy can be planned through the known remaining capacity, so that the lithium‐ion battery can be operated in the best working condition and the longest service life by adjusting the voltage and current 3 . Therefore, real‐time and accurate estimation of the SOC will provide significant help to battery management 4–6 . However, due to the complex internal structure of the lithium‐ion battery itself, the SOC of the lithium‐ion battery is affected by various complex factors such as self‐discharge current, self‐discharge effect, internal temperature, external ambient temperature, and battery aging, which makes it difficult to accurately estimate out the value of SOC 7,8 .…”

“…3 Therefore, real-time and accurate estimation of the SOC will provide significant help to battery management. [4][5][6] However, due to the complex internal structure of the lithium-ion battery itself, the SOC of the lithium-ion battery is affected by various complex factors such as self-discharge current, self-discharge effect, internal temperature, external ambient temperature, and battery aging, which makes it difficult to accurately estimate out the value of SOC. 7,8 In order to accurately estimate the SOC of lithium-ion batteries, relevant scholars have conducted a lot of research and proposed many methods for SOC estimation.…”