Reliable state of charge estimation of battery packs using fuzzy adaptive federated filtering

Hu, Luojia; Hu, Xiaosong; Che, Yunhong; Feng, Fei; Lin, Xianke; Zhang, Zhiyong

doi:10.1016/j.apenergy.2020.114569

Cited by 108 publications

(40 citation statements)

References 38 publications

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“…Different types of drivers show different characteristics in these indexes so that the main factor components can be extracted from these indexes and the drivers' classification characteristics can be decided with the method of clustering. According to historical data analysis results, [39][40][41][42] the drivers can be divided into three categories.…”

Section: Classification Of Driver Behavior Characteristicsmentioning

confidence: 99%

Research on risky driving behavior evaluation model based on CIDAS real data

Bao

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part D:

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This paper constructs an evaluation system that reflects dangerous driving behavior. The evaluation system has a three-layer structure model of “Evaluation Index-Performance Mode-Driving behavior score.” Verification of the feasibility of the model based on the relationship between the driver and the cause of the accident based on behavioral characteristics. First, the driving return survey data and accident form information of the real traffic accident cases of China In-Depth Accident Study (CIDAS) database are counted, and the character variables are converted into digital variables. Then, a three-tier structure of the dangerous driving behavior evaluation system is built, and the correlation between the driver and the cause of the accident is conducted to verify the feasibility of the model. The research shows that the individual characteristics of drivers with dangerous driving behavior are closely related to the cause of accidents, and the evaluation system constructed in this paper can quantify and describe this relationship effectively.

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Section: Classification Of Driver Behavior Characteristicsmentioning

confidence: 99%

Research on risky driving behavior evaluation model based on CIDAS real data

Bao

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part D:

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“…The widely used solutions include Kalman filter (KF), proportional-integral (PI) observer [10], H-infinite filter (HIF) [11], particle filter (PF) [12] as well as their extensions [13]. As well known, extended Kalman filter (EKF) is a classical observation algorithm for SOC estimation of lithium-ion batteries, and it mainly employs the partial derivatives to linearize the nonlinear electrical characteristics of batteries [14]. Nevertheless, the noise covariance of process and measurement are assumed to be constant values, thus reducing the estimation precision and incurring error divergence.…”

Section: Of 30mentioning

confidence: 99%

Stage of Charge Estimation of Lithium-Ion Battery Packs Based on Improved Cubature Kalman Filter With Long Short-Term Memory Model

Shu

Zhang

et al. 2021

IEEE Trans. Transp. Electrific.

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Accurate estimation of state of charge (SOC) of lithium-ion battery packs remains challenging due to inconsistencies among battery cells. To achieve precise SOC estimation of battery packs, firstly, a long short-term memory (LSTM) recurrent neural network (RNN)-based model is constructed to characterize the battery electrical performance, and a rolling learning method is proposed to update the model parameters for improving the model accuracy. Then, an improved square root-cubature Kalman filter (SRCKF) is designed together with the multi-innovation technique to estimate battery cell's SOC. Next, to cope with inconsistencies among battery cells, the SOC estimation value from the maximum and minimum cells are combined with a smoothing method to estimate the pack SOC. The robustness and accuracy of the proposed battery model and cell SOC estimation method are verified by exerting the experimental validation under time-varying temperature conditions. Finally, real operation data are collected from an electric-scooter (ES) monitoring platform to further validate the generalization of the designed pack SOC estimation algorithm. The experimental results manifest that the SOC estimation error can be limited within 2% after convergence.

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“…When the pressure difference is active, the system will select a larger duty cycle in order to quickly increase or reduce hydraulic cylinder pressure. When the pressure difference is positive, the system will choose a smaller duty cycle to accurately track the ideal pressure, and to improve the wheel pressure accuracy and robustness [37,38], specifically as listed in Table 2, where X is the pressure difference, Y1 is the valve duty signal of the booster valve, and Y2 is the duty cycle of the valve control signal of the pressure reducing valve.…”

Section: Braking Controllermentioning

confidence: 99%

Adaptive Cruise Control Strategy Design with Optimized Active Braking Control Algorithm

Zou

et al. 2020

Mathematical Problems in Engineering

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The braking quality is considered as the most important performance of the adaptive control system that influences the vehicle safety and ride comfort remarkably. This research is aimed at designing an adaptive cruise control (ACC) system based on active braking algorithm using hierarchical control. Taking into account the vehicle with safety and comfort, the upper decision-making controller is designed based on model predictive control algorithm. Throttle controller and braking controller are designed with feedforward and feedback algorithms as the bottom controller, where the braking controller is designed based on the hydraulic braking model. The whole model is simulated collaboratively with Amesim, Carsim, and Simulink. By comparison with the full deceleration model, the results show that the proposed algorithm can not only make the vehicle maintain a safe distance under the premise of following the target vehicle ahead effectively but also provide favorable driving comfort.

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Reliable state of charge estimation of battery packs using fuzzy adaptive federated filtering

Cited by 108 publications

References 38 publications

Research on risky driving behavior evaluation model based on CIDAS real data

Research on risky driving behavior evaluation model based on CIDAS real data

Stage of Charge Estimation of Lithium-Ion Battery Packs Based on Improved Cubature Kalman Filter With Long Short-Term Memory Model

Adaptive Cruise Control Strategy Design with Optimized Active Braking Control Algorithm

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