Numerical Study of Thermal Charging Supercapacitors Based on Cyclic Voltammetry

doi:10.12096/j.2096-4528.pgt.24058

Abstract

Abstract:

Objectives The application of thermal charging supercapacitors in energy storage is constrained by the ionic characteristics of the electrolyte. This study aims to explore the impact of electrolyte ionic characteristics on the capacitance performance and power density of the device. Based on the principle of cyclic voltammetry, a numerical model for the thermal charging supercapacitors is developed using multi-physics field numerical simulation methods. Methods The effects of ion size ratio and ion type on capacitance performance and power density are investigated separately, and the variation pattern of cation concentration at the electrode solid-liquid interface under a given temperature difference is summarized. Results The current density and specific capacitance of thermal charging supercapacitors decrease as ion size ratio increases at low scan rates. At this point, the power density is mainly affected by the ion size ratio, and it decreases as the ion size ratio increases. At high scan rates, power density is mainly affected by the ion type. Conclusions This study proposes an optimization strategy for electrolyte ionic characteristics, which is important for numerical modeling and theoretical analysis of thermal charging supercapacitors.

Key words: waste heat power generation technology, supercapacitors, cyclic voltammetry, numerical model, ionic characteristic, current density, power density, capacitive performance

CLC Number:

TK 02

Shigang BIAN, Tingting MENG, Lili YANG. Numerical Study of Thermal Charging Supercapacitors Based on Cyclic Voltammetry[J]. Power Generation Technology, 2025, 46(6): 1176-1183.

Figures/Tables 11

Fig. 1 Structure of thermal charging supercapacitors

Tab. 1 Geometric parameters of the numerical model

参数	数值
计算单元宽度/μm	1 000
计算单元高度/μm	270
负极厚度/μm	30
隔膜厚度/μm	50
上下电解质域厚度/μm	80
正极厚度/μm	30

Fig. 2 Boundary conditions for the numerical model

Tab. 2 Computational parameters of the numerical model

参数	数值
阳离子电荷z₁/C	1.6×10^-9
阴离子电荷z₂/C	1.6×10^-9
单位体积离子浓度c₀/(mol/L)	1
电解液离子扩散系数/(m²/s)	$D 1 T$
正极离子扩散系数/(m²/s)	$D 2 T$
负极离子扩散系数/(m²/s)	$D 3 T$
低温热源温度T₀/K	298.150
高温热源温度T/K	303.150~348.150
线性电压扫描速率v/(V/s)	10^-3~10²
最小扫描电压V_min/V	0
最大扫描电压V_max/V	1.200

Tab. 2 Computational parameters of the numerical model

参数	数值
阳离子电荷z₁/C	1.6×10^-9
阴离子电荷z₂/C	1.6×10^-9
单位体积离子浓度c₀/(mol/L)	1
电解液离子扩散系数/(m²/s)	$D 1 T$
正极离子扩散系数/(m²/s)	$D 2 T$
负极离子扩散系数/(m²/s)	$D 3 T$
低温热源温度T₀/K	298.150
高温热源温度T/K	303.150~348.150
线性电压扫描速率v/(V/s)	10^-3~10²
最小扫描电压V_min/V	0
最大扫描电压V_max/V	1.200

Fig. 3 Grid independence analysis

Fig. 4 Numerical model validation

Fig. 5 Cyclic voltammetry curves for different ion size ratios at low scan rates

Fig. 6 Cyclic voltammetry curves of different cation sizes at high scan rates

Fig. 7 Variation of power density with ion type

Fig. 8 Variation of cation concentration with temperature difference

Fig. 9 Relationship between maximum cation concentration and temperature difference

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