Lithium element has attracted remarkable attraction for energy storage devices, over the past 30 years. Lithium is a light element and exhibits the low atomic number 3, just after hydrogen and helium in the periodic t...Lithium element has attracted remarkable attraction for energy storage devices, over the past 30 years. Lithium is a light element and exhibits the low atomic number 3, just after hydrogen and helium in the periodic table. The lithium atom has a strong tendency to release one electron and constitute a positive charge, as Li<sup> </sup>. Initially, lithium metal was employed as a negative electrode, which released electrons. However, it was observed that its structure changed after the repetition of charge-discharge cycles. To remedy this, the cathode mainly consisted of layer metal oxide and olive, e.g., cobalt oxide, LiFePO<sub>4</sub>, etc., along with some contents of lithium, while the anode was assembled by graphite and silicon, etc. Moreover, the electrolyte was prepared using the lithium salt in a suitable solvent to attain a greater concentration of lithium ions. Owing to the lithium ions’ role, the battery’s name was mentioned as a lithium-ion battery. Herein, the presented work describes the working and operational mechanism of the lithium-ion battery. Further, the lithium-ion batteries’ general view and future prospects have also been elaborated.展开更多
Negative electrodes of the Ni-metal hydride battery were made from hydrogen storage alloy Mm0.9Ti0. 1Ni3. 9Mn0.4Co0.4Al0.3 mod fied by coating with Ni or mixing with Co powder. The cell volume expansion of hexagonal s...Negative electrodes of the Ni-metal hydride battery were made from hydrogen storage alloy Mm0.9Ti0. 1Ni3. 9Mn0.4Co0.4Al0.3 mod fied by coating with Ni or mixing with Co powder. The cell volume expansion of hexagonal structure was about 12 % after coating with 11 % Ni on the alloy Surface,When this alloy was mixed with Co powder. the discharge capacity and the utilization efficiency of the hydrogen storage alloy increased. When the alloy was coated with 11 wt-% Ni and also mixed with 10 wt-% Co powder. the capacity decay for a small sealed cylindrical cell (AA size. 1 Ah) was only about 4 % after 200 cycles展开更多
The short life of electric vehicle(EV)batteries is an important factor limiting the popularization of EVs.A hybrid energy storage system(HESS)for EVs combines Li-ion batteries with supercapacitors,so that the supercap...The short life of electric vehicle(EV)batteries is an important factor limiting the popularization of EVs.A hybrid energy storage system(HESS)for EVs combines Li-ion batteries with supercapacitors,so that the supercapacitor shares the peak power during the starting and braking,effectively solving the problem of irreversible capacity degradation of Li-ion batteries.Herein,an energy management strategy for HESS was designed based on battery degradation to extend the service life of the EV battery.First,to obtain accurate battery degradation characteristics,a cycling charge-discharge test was designed.Using this test,the effects of discharge rate and state of charge on battery degradation rate were determined,and the battery degradation model was constructed.Based on the working map of the motor obtained through the bench test,a data-based model of the power system was constructed to accurately characterize the energy consumption of the EV under different operating conditions.Second,rule-based and optimization-based energy management strategies that consider battery degradation were designed using the fuzzy algorithm and dynamic programming(DP)algorithm.The effectiveness of the devised control strategies was assessed using the model-in-the-loop and hardware-in-the-loop test platforms.The fuzzy control strategy had a simple structure and could be rapidly calculated but showed worse performance than the DP-based strategy in terms of battery degradation.The DP-based energy management strategy resulted in 16.68% lower capacity degradation than the fuzzy strategy.展开更多
Estimating the state-of-charge(SOC)of lithium-ion batteries faces three main challenges at present:ensuring accuracy,achieving smooth output,and maintaining low computational complexity.To tackle these issues,this stu...Estimating the state-of-charge(SOC)of lithium-ion batteries faces three main challenges at present:ensuring accuracy,achieving smooth output,and maintaining low computational complexity.To tackle these issues,this study introduces a hybrid algorithm observer.This approach combines the proportional-integral(PI)principle with the Kalman filter,utilizing a state-of-charge dynamics model and a current dynamics model.The SOC dynamics model,described by a differential equation,is developed to improve estimation accuracy.Meanwhile,the current dynamics model supports the design of a PI observer,which offers a low-complexity solution for SOC estimation.To address the issue of white noise in measurement signals,a onedimensional Kalman filter is applied.This filter smooths the output signal and enhances accuracy by addressing the limitations of the PI observer.In addition,the system incorporates parameter observation to estimate key battery parameters.The hybrid observer was tested in a real vehicle to validate its effectiveness.Experimental results and statistical analysis demonstrate that this algorithm is a strong candidate for accurately estimating SOC in lithium-ion batteries.展开更多
文摘Lithium element has attracted remarkable attraction for energy storage devices, over the past 30 years. Lithium is a light element and exhibits the low atomic number 3, just after hydrogen and helium in the periodic table. The lithium atom has a strong tendency to release one electron and constitute a positive charge, as Li<sup> </sup>. Initially, lithium metal was employed as a negative electrode, which released electrons. However, it was observed that its structure changed after the repetition of charge-discharge cycles. To remedy this, the cathode mainly consisted of layer metal oxide and olive, e.g., cobalt oxide, LiFePO<sub>4</sub>, etc., along with some contents of lithium, while the anode was assembled by graphite and silicon, etc. Moreover, the electrolyte was prepared using the lithium salt in a suitable solvent to attain a greater concentration of lithium ions. Owing to the lithium ions’ role, the battery’s name was mentioned as a lithium-ion battery. Herein, the presented work describes the working and operational mechanism of the lithium-ion battery. Further, the lithium-ion batteries’ general view and future prospects have also been elaborated.
文摘Negative electrodes of the Ni-metal hydride battery were made from hydrogen storage alloy Mm0.9Ti0. 1Ni3. 9Mn0.4Co0.4Al0.3 mod fied by coating with Ni or mixing with Co powder. The cell volume expansion of hexagonal structure was about 12 % after coating with 11 % Ni on the alloy Surface,When this alloy was mixed with Co powder. the discharge capacity and the utilization efficiency of the hydrogen storage alloy increased. When the alloy was coated with 11 wt-% Ni and also mixed with 10 wt-% Co powder. the capacity decay for a small sealed cylindrical cell (AA size. 1 Ah) was only about 4 % after 200 cycles
基金supported by the National Natural Science Foundation of China(Grant No.52272367).
文摘The short life of electric vehicle(EV)batteries is an important factor limiting the popularization of EVs.A hybrid energy storage system(HESS)for EVs combines Li-ion batteries with supercapacitors,so that the supercapacitor shares the peak power during the starting and braking,effectively solving the problem of irreversible capacity degradation of Li-ion batteries.Herein,an energy management strategy for HESS was designed based on battery degradation to extend the service life of the EV battery.First,to obtain accurate battery degradation characteristics,a cycling charge-discharge test was designed.Using this test,the effects of discharge rate and state of charge on battery degradation rate were determined,and the battery degradation model was constructed.Based on the working map of the motor obtained through the bench test,a data-based model of the power system was constructed to accurately characterize the energy consumption of the EV under different operating conditions.Second,rule-based and optimization-based energy management strategies that consider battery degradation were designed using the fuzzy algorithm and dynamic programming(DP)algorithm.The effectiveness of the devised control strategies was assessed using the model-in-the-loop and hardware-in-the-loop test platforms.The fuzzy control strategy had a simple structure and could be rapidly calculated but showed worse performance than the DP-based strategy in terms of battery degradation.The DP-based energy management strategy resulted in 16.68% lower capacity degradation than the fuzzy strategy.
基金supported by the Key Research and Development Program of Jiangsu Province(Grant No.BE2021006-2)the Key Science and Technology Program of Anhui Province(Grant No.202423d12050001)+1 种基金the Natural Science Foundation of Anhui Province(Grant No.2308085ME163)the National Natural Science Foundation of China(Grant No.62103415)。
文摘Estimating the state-of-charge(SOC)of lithium-ion batteries faces three main challenges at present:ensuring accuracy,achieving smooth output,and maintaining low computational complexity.To tackle these issues,this study introduces a hybrid algorithm observer.This approach combines the proportional-integral(PI)principle with the Kalman filter,utilizing a state-of-charge dynamics model and a current dynamics model.The SOC dynamics model,described by a differential equation,is developed to improve estimation accuracy.Meanwhile,the current dynamics model supports the design of a PI observer,which offers a low-complexity solution for SOC estimation.To address the issue of white noise in measurement signals,a onedimensional Kalman filter is applied.This filter smooths the output signal and enhances accuracy by addressing the limitations of the PI observer.In addition,the system incorporates parameter observation to estimate key battery parameters.The hybrid observer was tested in a real vehicle to validate its effectiveness.Experimental results and statistical analysis demonstrate that this algorithm is a strong candidate for accurately estimating SOC in lithium-ion batteries.
