Lithium-ion battery technology is the main leader in the market for electric vehicles. The performance, lifetime, and production costs of the cells are the major bottlenecks for the industry in the transition to a net zero future where the transportation systems are contributing minorly to negative climate change. Lithium-ion battery cell manufacturing includes various steps of material exploration, formulation design, slurry mixing, coating, drying, calendering, cutting, assembling, electrolyte filling, cell formation, and tests. Following the manufacturing processes, modelling batteries, and estimating their performance is critical for their integration into various applications. Advanced experimental techniques for measuring and quantifying factors, as well as the modern modelling strategies to simulate and demonstrate the relation between the variables and quality or performance are of great interest.
Considering the necessity and contribution of advanced manufacturing techniques as well as modelling and performance estimation methods, the focus of this Research Topic is on experimental and model-based techniques from cell design, to manufacturing and application.
The collection aims to host research and case studies around the challenges and opportunities in further research and development in battery manufacturing, including, but not limited to:
• Data-driven modelling methods
• Machine learning techniques
• Statistical analysis
• Multi-scale physics-based models
• Continuum models
• Manufacturing process modelling
• Manufacturing techniques
• State of charge, power, energy estimation.
• Thermal Models
• Electrical Models
• Mechanical Models
Lithium-ion battery technology is the main leader in the market for electric vehicles. The performance, lifetime, and production costs of the cells are the major bottlenecks for the industry in the transition to a net zero future where the transportation systems are contributing minorly to negative climate change. Lithium-ion battery cell manufacturing includes various steps of material exploration, formulation design, slurry mixing, coating, drying, calendering, cutting, assembling, electrolyte filling, cell formation, and tests. Following the manufacturing processes, modelling batteries, and estimating their performance is critical for their integration into various applications. Advanced experimental techniques for measuring and quantifying factors, as well as the modern modelling strategies to simulate and demonstrate the relation between the variables and quality or performance are of great interest.
Considering the necessity and contribution of advanced manufacturing techniques as well as modelling and performance estimation methods, the focus of this Research Topic is on experimental and model-based techniques from cell design, to manufacturing and application.
The collection aims to host research and case studies around the challenges and opportunities in further research and development in battery manufacturing, including, but not limited to:
• Data-driven modelling methods
• Machine learning techniques
• Statistical analysis
• Multi-scale physics-based models
• Continuum models
• Manufacturing process modelling
• Manufacturing techniques
• State of charge, power, energy estimation.
• Thermal Models
• Electrical Models
• Mechanical Models
