Electrification of go-kart with second-life lithium-ion batteries: Performance analysis and optimisation

This research paper presents the design, modelling, and performance analysis of an electric go-kart retrofitted with a second-life lithium-ion battery pack. A 10 kW brushless DC (BLDC) motor and a 50.4 V, 100 Ah repurposed battery pack (14S5P NMC configuration) form the core of the powertrain. Technical performance measurements achieved included a top speed of 67 km/h and peak acceleration of 9 m/s², demonstrating that the electrification of a go-kart with repurposed second-life cells was on par with or even improved over conventional internal combustion engine (ICE) go-karts. Through the first principle, theoretical modelling of resistive forces and drivetrain dynamics, the selection of a 4:1 gear ratio was determined to produce a required wheel torque of 122 N·m to meet performance targets. The pack delivered up to 287 A during peak acceleration with an acceptable voltage sag from 52 V to 41 V. Real-time telemetry monitored speed, current, voltage, and battery temperature, providing insight into the current state of the battery during testing. Thorough safety measures, including a battery management system (BMS), ensure that safety concerns are mitigated. The results demonstrate that second-life lithium-ion cells can be successfully reused in a dynamic, high-power application without significant performance compromise. This work offers a sustainable approach to recreational vehicle electrification and performance optimisation through modelling and simulation, highlighting how battery reuse can reduce costs and environmental impact while delivering competitive performance.

Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2025-11-25
DOI
https://doi.org/10.1051/matecconf/202541708005/pdf
Primary Topic
Electric and Hybrid Vehicle Technologies
Type
article
Field-Weighted Citation Impact
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article

Electrification of go-kart with second-life lithium-ion batteries: Performance analysis and optimisation

Springer Link (Chiba Institute of Technology)
Electric and Hybrid Vehicle Technologies
article

Electrification of go-kart with second-life lithium-ion batteries: Performance analysis and optimisation

article en

Abstract

This research paper presents the design, modelling, and performance analysis of an electric go-kart retrofitted with a second-life lithium-ion battery pack. A 10 kW brushless DC (BLDC) motor and a 50.4 V, 100 Ah repurposed battery pack (14S5P NMC configuration) form the core of the powertrain. Technical performance measurements achieved included a top speed of 67 km/h and peak acceleration of 9 m/s², demonstrating that the electrification of a go-kart with repurposed second-life cells was on par with or even improved over conventional internal combustion engine (ICE) go-karts. Through the first principle, theoretical modelling of resistive forces and drivetrain dynamics, the selection of a 4:1 gear ratio was determined to produce a required wheel torque of 122 N·m to meet performance targets. The pack delivered up to 287 A during peak acceleration with an acceptable voltage sag from 52 V to 41 V. Real-time telemetry monitored speed, current, voltage, and battery temperature, providing insight into the current state of the battery during testing. Thorough safety measures, including a battery management system (BMS), ensure that safety concerns are mitigated. The results demonstrate that second-life lithium-ion cells can be successfully reused in a dynamic, high-power application without significant performance compromise. This work offers a sustainable approach to recreational vehicle electrification and performance optimisation through modelling and simulation, highlighting how battery reuse can reduce costs and environmental impact while delivering competitive performance.

Springer Link (Chiba Institute of Technology)
Openalex Percentile: Top 48%
Electric and Hybrid Vehicle Technologies
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Electrification of go-kart with second-life lithium-ion batteries: Performance analysis and optimisation · Springer Link (Chiba Institute of Technology) (2025) | TGRS Research Map | TGRS