Future research avenues based on thematic clustering
| Key area | Research gap | Future research direction |
|---|---|---|
| Niche themes | ||
| Charging scheduling and blockchain | Limited real-world deployment of blockchain-integrated EV systems and lack of standardized protocols | Develop decentralized blockchain protocols aligned with charging networks and investigate user acceptance in pilot programs |
| Charge scheduling | Insufficient consideration of battery degradation and dynamic traffic conditions in charge scheduling models | Integrate battery lifecycle modeling with real-time stochastic scheduling for transit and fleet operations |
| Motor themes | ||
| EV and sustainability | Need for comprehensive models integrating sustainability metrics with infrastructure scalability | Propose integrated frameworks for smart grid connectivity, renewable use and carbon reduction within EV infrastructure |
| Emerging/declining themes | ||
| Electromobility | Limited empirical evidence from developing countries on stakeholder coordination and local governance | Conduct multi-stakeholder case studies to evaluate electromobility deployment across local governance structures |
| Electric vehicles and barriers | Lack of integrated frameworks addressing socio-economic and policy-related adoption barriers | Formulate multi-dimensional adoption models combining financial incentives, user education and infrastructure growth |
| Basic themes | ||
| Charging infrastructure and optimization | Scarcity of unified multi-criteria optimization frameworks combining routing, energy sources and location strategies | Design hybrid optimization models incorporating environmental, spatial and operational trade-offs at network scale |
| Electric vehicle charging | Lack of coordinated frameworks combining user behavior, grid constraints and charging station dynamics | Develop simulation-based decision tools to model interaction between user demand, grid load and infrastructure capacity |
| Charging stations and energy management strategy | Need for adaptive energy management strategies under varied operational contexts and emerging demand profiles | Explore AI-driven adaptive scheduling and demand response models tailored for urban and rural energy ecosystems |
| Battery electric vehicle and electric mobility | Insufficient integration of BEVs in long-term strategic planning and limited life-cycle assessments in diverse regions | Apply scenario-based modeling and dynamic LCA approaches to assess BEV deployment impacts in different regional contexts |
| Key area | Research gap | Future research direction |
|---|---|---|
| Charging scheduling and blockchain | Limited real-world deployment of blockchain-integrated EV systems and lack of standardized protocols | Develop decentralized blockchain protocols aligned with charging networks and investigate user acceptance in pilot programs |
| Charge scheduling | Insufficient consideration of battery degradation and dynamic traffic conditions in charge scheduling models | Integrate battery lifecycle modeling with real-time stochastic scheduling for transit and fleet operations |
| EV and sustainability | Need for comprehensive models integrating sustainability metrics with infrastructure scalability | Propose integrated frameworks for smart grid connectivity, renewable use and carbon reduction within EV infrastructure |
| Electromobility | Limited empirical evidence from developing countries on stakeholder coordination and local governance | Conduct multi-stakeholder case studies to evaluate electromobility deployment across local governance structures |
| Electric vehicles and barriers | Lack of integrated frameworks addressing socio-economic and policy-related adoption barriers | Formulate multi-dimensional adoption models combining financial incentives, user education and infrastructure growth |
| Charging infrastructure and optimization | Scarcity of unified multi-criteria optimization frameworks combining routing, energy sources and location strategies | Design hybrid optimization models incorporating environmental, spatial and operational trade-offs at network scale |
| Electric vehicle charging | Lack of coordinated frameworks combining user behavior, grid constraints and charging station dynamics | Develop simulation-based decision tools to model interaction between user demand, grid load and infrastructure capacity |
| Charging stations and energy management strategy | Need for adaptive energy management strategies under varied operational contexts and emerging demand profiles | Explore AI-driven adaptive scheduling and demand response models tailored for urban and rural energy ecosystems |
| Battery electric vehicle and electric mobility | Insufficient integration of BEVs in long-term strategic planning and limited life-cycle assessments in diverse regions | Apply scenario-based modeling and dynamic LCA approaches to assess BEV deployment impacts in different regional contexts |
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