|
Getting your Trinity Audio player ready...
|
The vital practice of using electric vehicles (EVs) is surpassing the sales of traditional automakers building internal combustion engines. The projected growth of EVs is expected to occupy 51% of the market share by 2030. And 60% of industries today are leveraging AI & data science technologies to map their EV’s performance test results.
The popularity of electric vehicles has significantly increased with time. And with the increasing demand for electric vehicles, the automotive industry is leveraging advanced technologies to map their customer interest and upgrade the existing prototypes. These advancements are causing changes not only in the transportation industry but also in business and society.
Integrating technology is transforming the transportation and automotive industry through tracking, analyzing, and evaluating the EV’s demographical data. The EV’s demographical data includes; charging station statistics, battery characteristics, energy consumption analysis, s characteristics, and route profile. The up-gradation of EVs is a prior challenge to surpass the obstacles like battery capacity, battery price, charging time, and availability of charging stations to use the full potential of EVs. The concept of EVs is not widely accepted yet and in many countries, the deployment of EVs is in the development stage. Leveraging data science and AI tech could help in performing better operations than expected.
Role of Data Science in the Electric Vehicle Domain (EVs)
The role and predominance of data have a significant impact on every industry. The increase in the amount of data generated, especially in transportation. Through the electrification of vehicles after the second industrial revolution; the transportation industry promised in developing better information systems for optimizing energy consumption in highly complex environments.
The sustainable growth of data in the EV domain has a significant impact on conducting insightful research. Car manufacturers, governments, and charging infrastructure providers are leveraging data analytics and data science tools to harness and analyze the available data to provide optimal EV services. Here are a few insights on leveraging data science and data analytical techniques in electric vehicles.
1. Predictive analytics for maintenance:
AI and data science technologies are disrupting the EV battery technology space, by combining the power of predictive analytics and data intelligence. The tech integration aims at achieving high battery efficiency and operational reliability. OEMs, battery pack manufacturers, electric fleet managers, and electric vehicle makers are leveraging predictive analytics tools. Data science, AI, and big data tools remarkably improve their end product performance and help in receiving better ROI at every stage of the product life-cycle.
2. Analytics is the key to unlocking EV demand:
The authorization and role of data are rapidly entering the space of energy, IT, transportation, Security, and other interconnected industries. Leveraging data has the potential to unlock, the system-level understanding of how these industries function. And analyzing the real-world data helped in better understanding mapping charging networks, optimizing transportation networks, transportation utilities, etc. Analyzing and interpreting EV market fluctuations and statistics is helping the stakeholders to improve their decision-making and reduce the rate of risk.
3. Data science and smart grid technologies:
The emerging use-case of data science technologies in the space of EV development has a greater impact on the current market scenario. The smart grid or super grid is an effective solution to meet the power system demand and reduce carbon emissions. The change from the robust combustion engine to the green energy consumption engine has a powerful impact on the human environment. Data analytics based on renewable energy forecasting methods are the hotcakes for better regulation and dispatch planning. The data collected from sensors and in-built trackers are helping in estimating customer behavior analysis, demand forecasting, and energy generation optimization.
The article describes data science’s importance centered on electric vehicles. The data science applications and use cases widen the space of research for every industry. And in the EV domain, it is leveraged to solve various EV-related challenges. The EV industry is at its early stage of development and integrating technologies can upgrade the niche areas of research and development. The data generated from many sources like road sensors, vehicles, and EV charging stations catalyzes high-quality data-driven research. The insights driven by research optimization have the opportunity to optimize EV space and in building risk-free models to make value-adding decisions.
The application of data science in the automotive space is more than a trend today. As the EV industry undergoes digital transformation and customer preferences evolve, data science-integrated manufacturing operations, marketing strategies, and charging point optimization is a necessity today. Soulpage, an on-demand EVnet solution, can provide quick insights about EV demographics and advanced data science capabilities to industries to meet additional challenges and explore new opportunities ahead. To know more about our product and to book a demo, click here.
If you need any help with idea validation, proof-of-concept, Data Science consulting, large-scale AI implementation, Big Data Engineering, or a creative solution for your Electric Vehicle Ecosystem. You are at the right place.
Talk to our experts