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A new generation of systems with integrated computational and physical capabilities that can communicate with people via a variety of new modalities is referred to as cyber-physical systems (CPS). Future technological advancements will be greatly aided by our ability to interact with the physical environment and enhance its capabilities through computing, communication, and control. The design and development of next-generation electric vehicle and hybrid gas-electric cars, completely autonomous city driving, and prosthetics that enable brain impulses to operate actual objects are examples of opportunities and research problems.
Figure 1 shows the CPS associated with EV. It’s basically the exchange of communication, commands, status, and real-time data between the physical layer and the cyber layer of EV.
Figure 1. CPS in EV
Characteristics of CPS that help EV strengthen its overall architecture:
The CPS plays a vital role in improving the overall architecture of EV and its platform. Some important characteristics that enhance the EV towards better future mobility are stated below:
· Advancement through learning based approach: The necessity for CPS design based on data-driven learning is highlighted by an expanding volume of CPS data, along with the requirement for adaptable systems that can handle dynamic settings. Such learning does, however, need the use of formal procedures that can ensure proper functioning as well as principled model-based design. Future design automation approaches that are based on learning will be developed, which is a crucial requirement. Learning-based systems perform far better than trained systems. Every time, the system will learn from past datasets while reducing the chances of error and enhance EV safety.
· Increases system size through scalability: As per the data by Deloitte the total number of EV sales are predicted to increase to 1,644,000 units in FY25 and 15,331,000 units by 2030. By utilising cloud computing features, CPSs can be scaled to meet demand. Users don’t need to look into the extra resources because they can get the required infrastructure. Because they can incorporate both computational and physical dynamics, CPSs are intrinsically diverse.
· Optimizing the system through one touch: CPS lays the foundation for a complete EV ecosystem to be updated and optimised with minimal effort. Over the past few decades, optimisation has played a vital role in increasing system productivity. As the EV segment is seeing a large jump in scalability, we need a platform from which complete monitoring and possible changes can be made while keeping the overall budget economical. This capability can be easily provided using the CPS infrastructure.
· Reducing time response to ensure safety: Due to their quick processing and the connectivity between sensors and cloud infrastructures, CPSs can respond quickly, which enables the early detection of remote faults and the efficient use of shared resources. This increases the safety features of the EV environment.
Challenges need to be addressed in EV-CPS:
Although, there is lot of scope of CPS in EV but still this topic need a much deeper research to overcome the challenges by CPS with EV integration. The integration of CPS with EV research is still in its early stages. Professional and institutional barriers have led to the creation of academic research and education spaces that are strictly defined and discipline-specific. Separate sub-disciplines of research, including as sensors, networking and communications, control theory, mathematical concepts, software engineering, and computer science, are studied separately. Figure 2, shows the challenges associated with EV-CPS.
Figure 2. Challenges with EV-CPS
The challenges are discussed in brief:
· Distributed approach of CPS: In EV-CPS, each component can be separated and assembled with advanced components. This can create a mismatch when an old system is upgraded with newer versions of components. For this reason, the CPS must be capable of adopting any changes in the cyber and physical layers after ground implementation of the architecture is over.
· Dynamic nature of CPS: CPS has a dynamic work environment. CPS design and operations must adapt in this way to take into account environmental changes. Environments can act hostilely in order to disrupt operations and breach intended attributes.
· Hybrid Environment: Computing and physical processes are combined in a CPS. It takes sophisticated theory and methods to model, develop, and assess the CPS when discrete and continuous dynamics are combined.
· Adaptive: Understanding the dynamic nature of the environment and the dynamics of the system is essential for CPS. Designers can employ the most recent artificial intelligence and machine learning to adapt to changes in the environment.
· Heterogeneous nature: The cyber-physical system is made up of a variety of parts. These components cooperate with one another, and we must connect them to various platforms to allow for communication between them.This interfacing is a big challenge for connecting different components and devices with different inbuilt capability.
· Human interface: As EV-CPS has the capability to work autonomously, for some critical operations, it is still required to take commands from humans or use a human-in-loop system. The decision of whether to put humans in the loop or go completely autonomous is a challenging task.
Future Scope of EV on CPS:
The integration of cyber-physical systems (CPS) will revolutionise the capabilities of electric vehicles (EVs) in the future. Through the use of cutting-edge technology like artificial intelligence, machine learning, and real-time data analysis, CPS will improve the performance, safety, and connectivity of EVs. Electric vehicles (EVs) will advance in intelligence, efficiency, and seamless integration with the developing transportation network. Figure 3 shows the overall future scope of CPS on EV.
Figure 3. Future Scope of EV with CPS
The future scope of the EV-CPS can be described as follows:
· Strengthening the Battery Management System (BMS): Battery Management Systems (BMS) are set to make significant strides in the future thanks to cyber-physical systems (CPS). BMS is essential to ensuring that batteries operate effectively and safely as energy storage technologies advance. CPS, which combines physical elements with computational and communication systems, is expected to transform BMS in a number of ways.
The upcoming CPS for BMS will feature improved monitoring and control capabilities as one of its main features. CPS can offer real-time data on a variety of factors, including temperature, voltage, and state of charge, thanks to modern sensor technology. This makes it possible to precisely monitor the health and performance of the battery, enabling preventative maintenance and improving battery use. Additionally, CPS can use machine learning algorithms to analyse massive volumes of data, find trends, and forecast battery behaviour, increasing system effectiveness.
· State-of-art infotainment: As EVs become more and more popular, there is a growing need for cutting-edge infotainment systems that offer a seamless and engaging driving experience. CPS is slated to transform EV infotainment in a number of ways since it merges physical components with computational and communication technologies.
The incorporation of artificial intelligence (AI) and machine learning (ML) algorithms into the future CPS for EV entertainment is a crucial component. For the purpose of customising the infotainment experience, these technologies can analyse enormous volumes of data from numerous sources, including sensors, cameras, and human interactions. Driver preferences can be learned by AI, which can then be used to give personalised information and services. For instance, based on the driver’s mood, the system can automatically modify music playlists, or it might suggest nearby charging stations based on the battery’s condition.
· Superior Advanced Driver Assistance Systems (ADAS): ADAS technologies are essential for expanding driver convenience, increasing safety, and allowing autonomous driving capabilities. CPS is poised to transform ADAS in a number of crucial areas by fusing physical elements with computational and communication technologies.
The incorporation of artificial intelligence (AI) and machine learning (ML) algorithms is a crucial feature of the future CPS for EV ADAS. These technologies enable real-time object detection, recognition, and prediction by analysing massive volumes of sensor data, including inputs from cameras, radars, and LiDARs. ADAS systems may continuously learn from and adjust to complicated driving scenarios with the help of AI and ML, increasing accuracy and responsiveness. This improves overall vehicle safety by enabling systems like adaptive cruise control, lane-keeping assistance, and autonomous emergency braking.
· Maintaining safety and security: Electric vehicle (EV) security and safety could be much improved in the future thanks to cyber-physical systems (CPS). The importance of protecting against cyber threats and guaranteeing passenger safety grows as EVs become more widely used. CPS, which combines physical elements with computational and communication networks, is anticipated to fundamentally alter EV safety and security in a number of ways. The use of cutting-edge sensor technology is a critical component of the future CPS for EV safety. For complete situational awareness, CPS can make use of a variety of sensors, including cameras, LiDAR, radar, and ultrasonic sensors. These sensors continuously scan the area around the car to look for objects, people, and other cars.
CPS can enhance collision avoidance systems, enable precise target detection, and increase overall road safety by merging sensor data with artificial intelligence and machine learning algorithms.
Conclusion:
In summary, the development and application of cyber-physical systems (CPS) will have a significant impact on the use of electric cars (EVs). A wide range of advantages are provided by CPS for EVs, including greater safety and security, real-time monitoring, and control. With the use of cutting-edge technologies like artificial intelligence, machine learning, and real-time data analysis, CPS enables EVs to improve their intelligence, efficiency, and seamless integration with the changing transportation ecosystem. These innovations open the path for improved performance, greater energy efficiency, and a more sustainable transportation future. As CPS develops further, it has the potential to completely transform the EV market, spurring innovation and moving us closer to a cleaner and smarter mobility future.
With CPS, electric vehicle technology is ready to revolutionise transportation and provide future generations with a cleaner, more connected world.
References:
1. Lukasiewycz, Martin, Sebastian Steinhorst, Florian Sagstetter, Wanli Chang, Peter Waszecki, Matthias Kauer, and Samarjit Chakraborty. “Cyber-physical systems design for electric vehicles.” In 2012 15th Euromicro Conference on Digital System Design, pp. 477–484. IEEE, 2012.
2. Chakraborty, Samarjit, Mohammad Abdullah Al Faruque, Wanli Chang, Dip Goswami, Marilyn Wolf, and Qi Zhu. “Automotive cyber–physical systems: A tutorial introduction.” IEEE Design & Test 33, no. 4 (2016): 92–108.
3. Kupin, Andrey, Dennis Kuznetsov, Ivan O. Muzyka, and Yurii Kumchenko. “The Сoncept of a Cyber-Physical System for Intelligent Battery Health Assessment and Road Range Forecast.” In ICTERI, pp. 334–344. 2021.
4. Bolbot, Victor, Gerasimos Theotokatos, Luminita Manuela Bujorianu, Evangelos Boulougouris, and Dracos Vassalos. “Vulnerabilities and safety assurance methods in Cyber-Physical Systems: A comprehensive review.” Reliability Engineering & System Safety 182 (2019): 179–193.
5. Xie, Yong, Yu Zhou, Jing Xu, Jian Zhou, Xiaobai Chen, and Fu Xiao. “Cybersecurity protection on in‐vehicle networks for distributed automotive cyber‐physical systems: state‐of‐the‐art and future challenges.” Software: Practice and Experience 51, no. 11 (2021): 2108–2127.
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