Reimagining Urban Mobility: New Strategy Optimizes EV Charging and Swapping Infrastructure
As the global shift toward electric vehicles (EVs) accelerates, cities face mounting pressure to adapt their infrastructure to meet evolving transportation needs. With over 4.26 million new energy vehicles registered in China by mid-2023 and projections indicating that electric vehicle ownership could surpass 65 million by 2030, the demand for efficient, accessible, and user-friendly charging solutions has never been greater. Yet, despite rapid technological advancements and policy support, a persistent challenge remains: range anxiety. Drivers continue to worry about whether they can reach their destination or find a reliable place to recharge. This concern not only affects consumer confidence but also hinders broader adoption of EVs.
In response, researchers are turning to innovative strategies that leverage existing urban infrastructure to build a more sustainable and resilient EV ecosystem. A recent study published in the Journal of Chongqing University of Technology (Natural Science) presents a comprehensive optimization model that rethinks how cities can repurpose underutilized facilities—particularly gas stations and public parking areas—into next-generation EV charging and battery-swapping hubs.
Conducted by Dr. Dan Dan Hu and Jingze Kou from the School of Management at South-Central Minzu University in Wuhan, the research introduces a novel site selection and capacity determination framework designed to minimize costs while maximizing service coverage and user satisfaction. The approach is grounded in real-world data from Wuchang District, a densely populated urban area in central China, where 133 residential communities were analyzed as demand points across 20 existing gas stations and 58 parking lots serving as candidate sites for redevelopment.
What sets this study apart is its dual focus on both charging and battery-swapping technologies. While most current infrastructure planning emphasizes plug-in charging stations, the authors argue that battery swapping—where depleted batteries are exchanged for fully charged ones in minutes—offers a compelling alternative that better aligns with traditional refueling behaviors. In fact, modern automated swap stations, such as NIO’s second-generation models, can complete a battery exchange in just five minutes, closely mirroring the “refuel-and-go” experience drivers are accustomed to at conventional gas stations.
“People are used to the convenience of gas stations,” said Dr. Hu, lead author of the paper. “If we want to make EVs truly mainstream, we need to offer a comparable level of speed and reliability. That’s where battery swapping comes in—it’s fast, efficient, and minimizes downtime.”
However, the high upfront cost of building swap stations has historically limited their deployment. To address this, the research team developed a mathematical model that integrates multiple cost factors, including construction expenses, unmet demand penalties, and user waiting times, into a single optimization framework. By applying a genetic algorithm—a computational method inspired by natural selection—they were able to simulate thousands of potential configurations and identify the most cost-effective and service-efficient solutions.
The results revealed several key insights with significant implications for urban planners, policymakers, and private investors. First, the optimal solution for Wuchang District involved constructing three battery swap stations and 23 charging stations equipped with a total of 225 charging points. This configuration achieved a coverage rate of nearly 90%, meaning that 89.67% of daily EV energy demand in the area could be met within a one-kilometer radius of a designated facility.
Interestingly, despite the advantages of swapping technology, only 15% of the available gas stations were converted into swap hubs under the base scenario. The primary reason? Cost. At 1.5 million CNY (approximately $210,000 USD) per unit, the construction of a single swap station remains significantly more expensive than installing a cluster of charging points. However, sensitivity analysis conducted as part of the study demonstrated that reducing the unit cost of swap stations could dramatically shift the balance.
When the assumed construction cost was lowered to 750,000 CNY, the optimal number of swap stations increased to five. At 250,000 CNY—roughly one-sixth of the current market price—the model recommended converting 12 of the 20 gas stations into swap facilities, boosting the conversion rate to 60%. Even more importantly, the overall system cost decreased substantially, indicating that lower capital investment in swap infrastructure could lead to both improved service coverage and greater economic efficiency.
“This finding is crucial,” explained Kou, the study’s co-author and a graduate researcher specializing in EV infrastructure planning. “It shows that with targeted financial incentives—such as government subsidies or public-private partnerships—we can accelerate the adoption of battery swapping without compromising fiscal responsibility.”
The study also examined the role of charging station design, particularly the power rating of individual charging units. Contrary to the assumption that higher-power chargers (e.g., 120 kW) are always preferable, the analysis found that 60 kW units performed nearly as well in terms of coverage and cost-effectiveness. Given that not all EV models support ultra-fast charging and that higher-power equipment requires more robust grid connections and thermal management systems, the researchers concluded that 60 kW represents a more practical and balanced choice for widespread public deployment.
Another critical factor identified in the study was coverage range. When the effective service radius of each station was expanded from 1 km to 3 km, the model achieved 100% demand coverage—meaning every EV owner in the district would have access to a nearby charging or swapping option. This underscores the importance of strategic placement and the potential benefits of integrating mobility data, population density, and travel patterns into the planning process.
From a methodological standpoint, the use of a genetic algorithm allowed the researchers to navigate the complexity of the problem efficiently. Traditional optimization techniques often struggle with large-scale, non-linear problems like EV infrastructure planning, which involve numerous variables and constraints. In contrast, the genetic algorithm enabled rapid exploration of the solution space, balancing trade-offs between cost, coverage, and user convenience.
The implications of this research extend beyond Wuchang District. As cities worldwide grapple with the transition to zero-emission transportation, the idea of repurposing obsolete fossil fuel infrastructure offers a pragmatic path forward. Gas stations, once symbols of the petroleum era, could be transformed into hubs of clean energy innovation. Parking lots, long seen as passive urban elements, can evolve into active nodes in a dynamic charging network.
Moreover, the study highlights the importance of policy intervention in shaping market outcomes. Without financial support, the economic barriers to deploying advanced technologies like battery swapping may prove insurmountable. But with well-designed incentives, governments can catalyze private investment, drive down costs through economies of scale, and create a more equitable and resilient transportation system.
For automakers and charging network operators, the findings suggest a need for greater collaboration. Standardization of battery formats, interoperability between brands, and shared access to swap stations could further reduce costs and improve user experience. Companies like NIO, GAC Aion, and CATL have already begun exploring battery-as-a-service (BaaS) models, where consumers lease batteries instead of purchasing them outright—a shift that aligns perfectly with the swap-based infrastructure envisioned in the study.
Urban planners, too, stand to benefit from adopting such data-driven, adaptive approaches. Rather than relying on static zoning regulations or one-size-fits-all mandates, municipalities can use simulation tools to test different scenarios, evaluate trade-offs, and engage stakeholders in evidence-based decision-making. The integration of geographic information systems (GIS), real-time traffic data, and predictive analytics can further enhance the precision and responsiveness of infrastructure planning.
Looking ahead, the research team plans to expand their model to include additional variables, such as renewable energy integration, dynamic pricing, and multi-modal transportation networks. They also aim to apply the framework to other cities with different demographic and geographic profiles, testing its scalability and adaptability.
Ultimately, the success of the EV revolution will depend not just on better batteries or more powerful motors, but on smarter, more human-centered infrastructure. By reimagining what gas stations and parking lots can become, this study offers a blueprint for a future where clean mobility is not only possible—but convenient, affordable, and universally accessible.
As Dr. Hu noted, “The transition to electric vehicles isn’t just about changing the way cars are powered. It’s about transforming the entire ecosystem around them. We have the tools, the data, and the opportunity to build something better. Now we need the vision and the will to make it happen.”
The work of Hu and Kou serves as a timely reminder that innovation doesn’t always require starting from scratch. Sometimes, the most sustainable solutions come from reusing what’s already there—adapting yesterday’s infrastructure for tomorrow’s challenges.
Reimagining Urban Mobility: New Strategy Optimizes EV Charging and Swapping Infrastructure
Dan Dan Hu, Jingze Kou, School of Management, South-Central Minzu University; Journal of Chongqing University of Technology (Natural Science), DOI: 10.3969/j.issn.1674-8425(z).2024.05.004