Electric Vehicle Intelligent Charging Technology Subverts Car Park Profit Models

Electric Vehicle Intelligent Charging Technology Subverts Car Park Profit Models

With the increasing popularity of electric vehicles (EVs), drivers in Hong Kong now demand higher-quality and more abundant EV charging facilities in parking lots than ever before.

As a result, many large shopping malls are proactively installing additional charging stations in their parking lots, including chargers for tourist buses, to attract more tourists and cater to the growing number of EV owners.

A Brand New Profit Model to Enhance the Value of Fixed Assets

In the past, charging stations in parking lots mainly contributed to increased foot traffic. However, with technological advancements and the development of artificial intelligence, coupled with decreasing management costs, car parks have started profiting from reselling electricity after getting approval from the authorities. This revenue even surpasses the income generated from merely renting out parking spaces, making it an attractive option for property developers to increase the value of their fixed assets.

Currently, there are generally two profit models for reselling EV electricity in the market: hourly charging for parking spaces and charging based on the actual electricity usage per kilowatt-hour.

Let us take some rapid EV charging stations in car parks in the commercial areas as examples. In these areas, the standard fee for hourly charging is HK$150 (based on an output of 50 kW, with HK$3 per kWh). Considering the current market demand for charging spaces and deducting the installation cost of charging facilities, the investment on a rapid EV charging station can be recouped within 2 to 3 years. This timeframe is approximately 20 years faster than relying solely on parking lot rentals (based on the average market price of HK$1.8 million for purchasing a parking lot, with a 3% annual return on investment rate).

However, when assessing the return on investment for these charging facilities, it is essential to consider not only their installation cost but also other objective factors, such as the car park’s electricity distribution capacity and the feasibility of the power supply system. These factors have a significant impact on the overall profitability.

Intelligent Load Management System Empowered by AI-Learning Enables Lower Investment Thresholds and Diverse Profit Model for Car Parks

In Hong Kong, many parking facilities are facing challenges with ageing infrastructure, especially concerning power supply and distribution. This necessitates renovation or the addition of extra power systems to support EVs, leading to financial burdens.

To address these issues, a team led by Professor Simon Yu and Dr. Nelson Chan from the Department of Aeronautical and Aviation Engineering of The Hong Kong Polytechnic University (PolyU) has developed an artificial intelligence (AI)-based power distribution system, namely AI Load Management System (AI-LMS). This system autonomously allocates electricity and adjusts the charging speed for EVs based on their individual charging requirements and other parameters, all while operating within the constraints of the available power supply.

To be more specific, the AI-LMS, with proper training, can forecast the parking facility's load conditions and allocate a specific amount of electricity to designated parking lots, thereby optimizing time and energy usage. As shown in Tables 1 and 2 below, a comparison of charging scenarios with and without the presence of AI-LMS demonstrates the system's efficiency and benefits.

By incorporating AI technology into the parking environment, the system efficiently charges 2 EVs with shorter parking times at the maximum rate while continuing to charge other vehicles. The final results show that: (1) the charging time for the 2 EVs is vastly reduced by 1 hour and 43 minutes (i.e. 4:34 – 2:51), (2) the remaining 3 EVs can be fully charged by just using 4 minutes more (i.e. 4:38 – 4:34), still within their predicted parking times, and (3) the overall charging time is significantly reduced by more than 3 hours.

Table 1: Charging environment without AI-LMS
Total Three-phase Electricity Supply in the Car Park (ampere)	100
Number of Parking Lots	5
EV's Battery Capacity (kWh)	60
Maximum Three-phase Charging Current of EV Charger (ampere)	32
Average Three-phase Charging Current of EV Charger (ampere)	20
Average Charging Time (hour)	4:34
Total Charging Time Recorded in the Car Park (hour)	22:49

Table 2: Charging environment with AI-LMS
Total Three-phase Electricity Supply in the Car Park (ampere)	100
Number of Parking Lots	2	3
Car Parking Duration Forecasted by AI-LMS (hour)	3	5
Intelligent Allocation of Three-phase Charging Current (ampere)	32	12 to 32
Average Charging Time (hour)	2:51	4:38
Total Charging Time Recorded in the Car Park (hour)	19:36

Featured with flexible payment methods, the AI-LMS can allocate electricity to designated parking spaces, enabling vehicle owners willing to pay an extra fee to enjoy faster charging services, thus diversifying the profit model.

Besides, this system operates without the need for human supervision, and the collection of data is processed in a manner that ensures data source confidentiality by not identifying individuals or vehicle models. Simultaneously, the system discreetly analyzes the usage data, providing management with substantial data for decision-making.

Reselling EV Electricity is the Future of Car Park Development

Currently, this system has been successfully implemented in the large car park in 11 SKIES. The team is now considering upgrading the existing system for other car parks, including the ones in PolyU, CLP Power, and Airport Authority Hong Kong (AAHK).

Using PolyU's car park project as an example, the existing 10 charging stations have a usage rate of approximately 56% per day (from 8:00 am to 8:00 pm) and are providing free charging services to staff members. To meet the substantial demand, PolyU is actively planning to expand the number of charging facilities and scaling up the coverage of the system. Moreover, the team has put forward some upgrade suggestions based on the existing technological frame and functionalities, such as (1) incorporating AI control and automatic three-phase load balancing system, and (2) additional features typically designed for PolyU, such as a self-service system that allows staff members to use their staff ID cards to configure service options for charging devices and paying fees through the system, thus contributing to carbon neutrality and fostering a smart campus life.

Dr. Nelson Chan, who possesses a strong engineering background from PolyU, expresses confidence in the maturity of the University's charging technology. With the incorporation of various charging standards tailored to practical applications, the system is poised to deliver enhanced stability and durability compared to conventional commercial systems.

Based on market feedback, conventional charging facilities usually require maintenance every 6 to 12 months, whereas it is every 2 to 3 years for PolyU's chargers, resulting in substantial maintenance cost reductions. Moreover, being developed by the academically proficient team of PolyU, the system is compatible with various device types, bringing true flexibility to car parks and enhancing energy efficiency.

He believes that the successful practical application of the system reflects the market's increasing emphasis on the quality and convenience of charging facilities. With the widespread adoption of wireless charging, big data, and artificial intelligence technologies, introducing intelligence into car parks is undoubtedly the prevailing trend.