Analysis and Improvement Measures of Driving Range Attenuation of Electric Vehicles in Winter

Mao, Shuoyuan; Han, Meilin; Han, Xiao; Jie, Shao; Lu, Yong; Lu, Languang; Ouyang, Minggao

doi:10.3390/wevj12040239

Cited by 11 publications

(7 citation statements)

References 19 publications

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“…Nevertheless, LIB suffer from a serious energy attenuation problem in low temperature, especially LFP batteries [7,8]. Qin et al reviewed the performance of batteries at low temperature and illustrated that the discharge capacity of LFP drops from 134.5 mAh/g (20 • C) to 90 mAh/g (−20 • C) [9], which corresponds to the authors' pre-experiment, as shown in Supplementary Material Figure S1.…”

Section: Introduction 1backgroundsmentioning

confidence: 85%

“…In this study, a two-state lumped parameter thermal model is constructed as the single cell model, the EKF algorithm is introduced as the closed-loop method to estimate the battery core temperature, and a network of single cells is connected to form the module model. The modeling is based on the battery pack of Wuling HongGuang Mini EV (SAIC GM Wuling Automobile Co., Ltd., Liuzhou, China) [8].…”

Section: Battery Thermal Modelmentioning

confidence: 99%

“…Training the neural network requires a lot of dynamic data. This study uses NEDC and FUDS dynamic test conditions, and it selects seven long-term and continuous current data from the real vehicle data set of a vehicle tested in winter of Beijing at year 2020 [8], respectively, to form a data set. All the current protocols are shown in Figure 6.…”

Section: Experiments Set-up and Battery Electrical Model Parameter Id...mentioning

confidence: 99%

“…The sum of the discharge energy of the cells is the RAE of the module under WLTC test condition. The battery preheating at low temperature is one way to increase available energy [8]. On the one hand, raising the temperature can lower the battery resistance and obtain energy recovery; on the other hand, heating the battery consumes the energy contained in the battery, so there is a trade-off relationship.…”

Section: Operation Condition-based Rae Calculation Algorithmmentioning

confidence: 99%

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An Electrical–Thermal Coupling Model with Artificial Intelligence for State of Charge and Residual Available Energy Co-Estimation of LiFePO4 Battery System under Various Temperatures

Mao

Han

et al. 2022

Batteries

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The LiFePO4 (LFP) battery tends to underperform in low temperature: the available energy drops, while the state of charge (SOC) and residual available energy (RAE) estimation error increase dramatically compared to the result under room temperature, which causes mileage anxiety for drivers. This paper introduces an artificial intelligence-based electrical–thermal coupling battery model, presents an application-oriented procedure to estimate SOC and RAE for a reliable and effective battery management system, and puts forward a model-based strategy to control the battery thermal state in low temperature. Firstly, an LFP battery electrical model based on artificial intelligence is proposed to estimate the terminal voltage, and a thermal resistance model with an EKF estimation algorithm is established to assess the temperature distribution in the battery pack. Then, the electrical and thermal models are coupled, a closed-loop EKF algorithm is employed to estimate the battery SOC, and a fusion method is discussed. The coupled model is simulated under a given protocol and RAE can be obtained. Finally, based on the electrical–thermal coupling model and RAE calculation algorithm, a preheating method and constant power condition-based RAE estimation are discussed, and the thermal management strategy of the battery system under low temperature is formed. Results show that the estimation error of SOC can be controlled within 2% and RAE can be controlled within 4%, respectively. The preheating strategy at low temperature and low SOC can significantly improve the energy output of the battery pack system.

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Section: Introduction 1backgroundsmentioning

confidence: 85%

Section: Battery Thermal Modelmentioning

confidence: 99%

Section: Experiments Set-up and Battery Electrical Model Parameter Id...mentioning

confidence: 99%

Section: Operation Condition-based Rae Calculation Algorithmmentioning

confidence: 99%

See 2 more Smart Citations

An Electrical–Thermal Coupling Model with Artificial Intelligence for State of Charge and Residual Available Energy Co-Estimation of LiFePO4 Battery System under Various Temperatures

Mao

Han

et al. 2022

Batteries

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“…[19] The 37.27% power loss of electric vehicles by using air-conditioning has also been reported. [20] The VIPV is thought to be useful for heat shielding.…”

Section: Effects Of Usage Of Air Conditioner Upon Driving Distance Of...mentioning

confidence: 99%

Analysis of Climate Conditions upon Driving Distance of Vehicle Integrated Photovoltaics‐Powered Vehicles

Yamaguchi,

Nakamura,

Ozaki

et al. 2023

Energy Tech

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The development of the vehicles powered by photovoltaic (PV) is desirable and very important for reducing CO2 emissions from the transport sector to realize a decarbonized society. Although long‐distance driving of vehicle‐integrated PV (VIPV)‐powered vehicles without electricity charging is expected in sunny regions, driving distance of VIPV‐powered vehicles is affected by climate conditions such as solar irradiation and outside temperature, and the power consumption of the air conditioners. In this article, analytical results for system efficiency of VIPV‐powered vehicles and the effects of usage of air conditioner are presented by using power losses estimated from the electric mileage by using the driving distance data for Toyota Prius and Nissan Van demonstration cars installed with high‐efficiency InGaP/GaAs/InGaAs three‐junction solar cell modules with a module efficiency of more than 30%. The potential of VIPV‐powered vehicles to be deployed in major cities in Japan and the world is also analyzed. Mild weather cities such as Miyazaki in Japan and Sydney in Australia are thought to have longer driving range even under usage of air conditioners. The other power losses for the VIPV such as temperature rise of VIPV modules and partial shading estimate the previous data and some reference as well as effects of usage of air‐conditioners are also discussed in this article.

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Analysis of fuel economy reduction factors of hybrid electric vehicles in winter using on-road driving data

Choi,

Cha,

Song

2024

Energy

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Analysis and Improvement Measures of Driving Range Attenuation of Electric Vehicles in Winter

Cited by 11 publications

References 19 publications

An Electrical–Thermal Coupling Model with Artificial Intelligence for State of Charge and Residual Available Energy Co-Estimation of LiFePO4 Battery System under Various Temperatures

An Electrical–Thermal Coupling Model with Artificial Intelligence for State of Charge and Residual Available Energy Co-Estimation of LiFePO4 Battery System under Various Temperatures

Analysis of Climate Conditions upon Driving Distance of Vehicle Integrated Photovoltaics‐Powered Vehicles

Analysis of fuel economy reduction factors of hybrid electric vehicles in winter using on-road driving data

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