Development of Real-Time Estimation of Thermal and Internal Resistance for Reused Lithium-Ion Batteries Targeted at Carbon-Neutral Greenhouse Conditions

Muhammad Bilhaq Ashlah, Chiao-Yin Tu, Chia-Hao Wu, Yulian Fatkur Rohman, Akhmad Azhar Firdaus, Won-Jung Choi and Wu-Yang Sean ()
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Muhammad Bilhaq Ashlah: Department of Bio-Industrial Mechatronic Engineering, National Chung Hsing University, Taichung City 40227, Taiwan
Chiao-Yin Tu: Department of Bio-Industrial Mechatronic Engineering, National Chung Hsing University, Taichung City 40227, Taiwan
Chia-Hao Wu: Department of Bio-Industrial Mechatronic Engineering, National Chung Hsing University, Taichung City 40227, Taiwan
Yulian Fatkur Rohman: Department of Bio-Industrial Mechatronic Engineering, National Chung Hsing University, Taichung City 40227, Taiwan
Akhmad Azhar Firdaus: Department of Bio-Industrial Mechatronic Engineering, National Chung Hsing University, Taichung City 40227, Taiwan
Won-Jung Choi: School of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology, Ulsan 44919, Republic of Korea
Wu-Yang Sean: Department of Bio-Industrial Mechatronic Engineering, National Chung Hsing University, Taichung City 40227, Taiwan

Energies, 2025, vol. 18, issue 17, 1-17

Abstract: The transition toward renewable-powered greenhouse agriculture offers opportunities for reducing operational costs and environmental impacts, yet challenges remain in managing fluctuating energy loads and optimizing agricultural inputs. While second-life lithium-ion batteries provide a cost-effective energy storage option, their thermal and electrical characteristics under real-world greenhouse conditions are poorly documented. Similarly, although plasma-activated water (PAW) shows potential to reduce chemical fertilizer usage, its integration with renewable-powered systems requires further investigation. This study develops an adaptive monitoring and modeling framework to estimate the thermal resistances ( R u , R c ) and internal resistance (R int ) of second-life lithium-ion batteries using operational data from greenhouse applications, alongside a field trial assessing PAW effects on beefsteak tomato cultivation. The adaptive control algorithm accurately estimated surface temperature ( T s ) and core temperature ( T c ), achieving a root mean square error (RMSE) of 0.31 °C, a mean absolute error (MAE) of 0.25 °C, and a percentage error of 0.31%. Thermal resistance values stabilized at R u ≈ 3.00 °C/W (surface to ambient) and R c ≈ 2.00 °C/W (core to surface), indicating stable thermal regulation under load variations. Internal resistance (R int ) maintained a baseline of ~1.0–1.2 Ω, with peaks up to 12 Ω during load transitions, confirming the importance of continuous monitoring for performance and degradation prevention in second-life applications. The PAW treatment reduced chemical nitrogen fertilizer use by 31.2% without decreasing total nitrogen availability (69.5 mg/L). The NO 3 − -N concentration in PAW reached 134 mg/L, with an initial pH of 3.04 neutralized before application, ensuring no adverse effects on germination or growth. Leaf nutrient analysis showed lower nitrogen (1.83% vs. 2.28%) and potassium (1.66% vs. 2.17%) compared to the control, but higher magnesium content (0.59% vs. 0.37%), meeting Japanese adequacy standards. The total yield was 7.8 kg/m 2 , with fruit quality comparable between the PAW and control groups. The integration of adaptive battery monitoring with PAW irrigation demonstrates a practical pathway toward energy efficient and sustainable greenhouse operations.

Keywords: second-life lithium-ion battery; internal resistance; thermal resistance; adaptive monitoring; greenhouse energy storage; plasma-activated water; sustainable agriculture (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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