A Data-Driven Power Management Strategy for Plug-In Hybrid Electric Vehicles Including Optimal Battery Depth of Discharging

Xie, Shaobo; Qi, Shanwei; Lang, Kun

doi:10.1109/tii.2019.2917468

Cited by 44 publications

(21 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For instance, a capacity loss model based on ampere-hour calculation is converted into equivalent hydrogen consumption in the energy control of a hybrid fuel cell electric bus in [6], and this capacity loss model is also applied in [7] to evaluate the impact of control strategies to battery degradation for electric buses. The same amperehour based capacity loss model is applied in [8] to minimize the PHEV energy consumption cost. A similar semiempirical capacity fade and resistance increase model is also applied in [9] to study the battery downsizing problem for PHEVs.…”

Section: Introductionmentioning

confidence: 99%

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

Zhang

2020

IEEE Access

View full text Add to dashboard Cite

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

show abstract

Section: Introductionmentioning

confidence: 99%

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

Zhang

2020

IEEE Access

View full text Add to dashboard Cite

show abstract

“…The above advantages of performance modeling, or called column counting or Ahthroughput battery aging method, has made it become very popular in literatures related in Optimal EMS of HEV with battery aging consideration [52][53][54][55][56][57][58][59][60][61][62][63][64]. Lithium-ion battery LiFePO4 will be studied in this brief due to its advantages in safety, and longer life characteristic [65].…”

Section: Optimal Ems Of Hev With Battery Aging Considerationmentioning

confidence: 99%

“…Similar to [54], a data driven method has been introduced based on five speed profiles collected from urban bus in [55]. Cost function in (2.3) has been used in a PMP optimal method.…”

Section: Optimal Ems Of Hev With Battery Aging Considerationmentioning

confidence: 99%

“…The aging coefficient is introduced as the purchasing cost of the battery system, which the cost of the battery has been decreased rapidly in these years according to the mature technology and the volume production for Lithium ion batteries in the industry [83]. It will be difficult to maintain in consistent with the proposed work in [54] [55]. In addition, Γ nom also used constant assumptions of nominal C-rate, SOC, and temperature in these papers.…”

Section: Optimal Ems Of Hev With Battery Aging Considerationmentioning

confidence: 99%

“…However, it is not applicable for general commercial vehicles with unknown or unpredictable drive cycles. Thus, the data driven method in [55] is only applicable for service vehicles with typical driving routines.…”

Section: Optimal Ems Of Hev With Battery Aging Considerationmentioning

confidence: 99%

See 2 more Smart Citations

Hybrid Electric Vehicle Energy Management Strategy with Consideration of Battery Aging

Zhou¹

View full text Add to dashboard Cite

show abstract

RETRACTED ARTICLE: Intelligent power management based on multi-objective cost function for plug-in biogas hybrid vehicles under uncertain driving conditions

Abd‐Elhaleem

Shoeib

Sobaih

2022

Complex Intell. Syst.

View full text Add to dashboard Cite

This paper presents a new intelligent power management strategy based on multi-objective cost function for plug-in biogas hybrid vehicles (PBHVs). This strategy consists of long-term power management and a short-term controller. The long-term power management depends on an improved generalized particle swarm optimization algorithm (IGPSO) to obtain the globally optimal values of motor and biogas engine torques. To reduce the computation time, five-mode rule-based control is used, where the IGPSO estimates the optimal values for the motor and engine torques in a hybrid mode depending on a multi-objective cost function. This cost function aims to reduce fuel consumption and the drawn current from the battery and takes into consideration the battery ageing. The short-term controller is designed using an interval type-2 Takagi–Sugeno-Kang (IT2TSK) fuzzy algorithm, which depends on human experts to overcome the uncertainties of the driving conditions. Lyapunov stability theory for the online controller is proved. The proposed technique improves the energy consumption compared to other techniques. The simulation results using real data for the engine, motor and battery illustrate the feasibility and effectiveness of the proposed approach with comparative results.

show abstract

A Data-Driven Power Management Strategy for Plug-In Hybrid Electric Vehicles Including Optimal Battery Depth of Discharging

Cited by 44 publications

References 30 publications

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

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

Hybrid Electric Vehicle Energy Management Strategy with Consideration of Battery Aging

RETRACTED ARTICLE: Intelligent power management based on multi-objective cost function for plug-in biogas hybrid vehicles under uncertain driving conditions

Contact Info

Product

Resources

About