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Rahman, S., Aburub, H., Mekonnen, Y., Sarwat, A. I..  2018.  A Study of EV BMS Cyber Security Based on Neural Network SOC Prediction. 2018 IEEE/PES Transmission and Distribution Conference and Exposition (T D). :1—5.

Recent changes to greenhouse gas emission policies are catalyzing the electric vehicle (EV) market making it readily accessible to consumers. While there are challenges that arise with dense deployment of EVs, one of the major future concerns is cyber security threat. In this paper, cyber security threats in the form of tampering with EV battery's State of Charge (SOC) was explored. A Back Propagation (BP) Neural Network (NN) was trained and tested based on experimental data to estimate SOC of battery under normal operation and cyber-attack scenarios. NeuralWare software was used to run scenarios. Different statistic metrics of the predicted values were compared against the actual values of the specific battery tested to measure the stability and accuracy of the proposed BP network under different operating conditions. The results showed that BP NN was able to capture and detect the false entries due to a cyber-attack on its network.

Fraiji, Yosra, Ben Azzouz, Lamia, Trojet, Wassim, Saidane, Leila Azouz.  2018.  Cyber security issues of Internet of electric vehicles. 2018 IEEE Wireless Communications and Networking Conference (WCNC). :1—6.

The use of Electric Vehicle (EV) is growing rapidly due to its environmental benefits. However, the major problem of these vehicles is their limited battery, the lack of charging stations and the re-charge time. Introducing Information and Communication Technologies, in the field of EV, will improve energy efficiency, energy consumption predictions, availability of charging stations, etc. The Internet of Vehicles based only on Electric Vehicles (IoEV) is a complex system. It is composed of vehicles, humans, sensors, road infrastructure and charging stations. All these entities communicate using several communication technologies (ZigBee, 802.11p, cellular networks, etc). IoEV is therefore vulnerable to significant attacks such as DoS, false data injection, modification. Hence, security is a crucial factor for the development and the wide deployment of Internet of Electric Vehicles (IoEV). In this paper, we present an overview of security issues of the IoEV architecture and we highlight open issues that make the IoEV security a challenging research area in the future.

Davydov, Vadim, Bezzateev, Sergey.  2018.  Secure Information Exchange in Defining the Location of the Vehicle. 2018 41st International Conference on Telecommunications and Signal Processing (TSP). :1—5.

With the advent of the electric vehicle market, the problem of locating a vehicle is becoming more and more important. Smart roads are creating, where the car control system can work without a person - communicating with the elements on the road. The standard technologies, such as GPS, can't always accurately determine the location, and not all vehicles have a GPS-module. It is very important to build an effective secure communication protocol between the vehicle and the base stations on the road. In this paper we consider different methods of location determination, propose the improved communicating protocol between the vehicle and the base station.

Rudolph, Hendryk, Lan, Tian, Strehl, Konrad, He, Qinwei, Lan, Yuanliang.  2019.  Simulating the Efficiency of Thermoelectrical Generators for Sensor Nodes. 2019 4th IEEE Workshop on the Electronic Grid (eGRID). :1—6.

In order to be more environmentally friendly, a lot of parts and aspects of life become electrified to reduce the usage of fossil fuels. This can be seen in the increased number of electrical vehicles in everyday life. This of course only makes a positive impact on the environment, if the electricity is produced environmentally friendly and comes from renewable sources. But when the green electrical power is produced, it still needs to be transported to where it's needed, which is not necessarily near the production site. In China, one of the ways to do this transport is to use High Voltage Direct Current (HVDC) technology. This of course means, that the current has to be converted to DC before being transported to the end user. That implies that the converter stations are of great importance for the grid security. Therefore, a precise monitoring of the stations is necessary. Ideally, this could be accomplished with wireless sensor nodes with an autarkic energy supply. A role in this energy supply could be played by a thermoelectrical generator (TEG). But to assess the power generated in the specific environment, a simulation would be highly desirable, to evaluate the power gained from the temperature difference in the converter station. This paper proposes a method to simulate the generated power by combining a model for the generator with a Computational Fluid Dynamics (CFD) model converter.

Lal Senanayaka, Jagath Sri, Van Khang, Huynh, Robbersmyr, Kjell G..  2018.  Multiple Fault Diagnosis of Electric Powertrains Under Variable Speeds Using Convolutional Neural Networks. 2018 XIII International Conference on Electrical Machines (ICEM). :1900–1905.
Electric powertrains are widely used in automotive and renewable energy industries. Reliable diagnosis for defects in the critical components such as bearings, gears and stator windings, is important to prevent failures and enhance the system reliability and power availability. Most of existing fault diagnosis methods are based on specific characteristic frequencies to single faults at constant speed operations. Once multiple faults occur in the system, such a method may not detect the faults effectively and may give false alarms. Furthermore, variable speed operations render a challenge of analysing nonstationary signals. In this work, a deep learning-based fault diagnosis method is proposed to detect common faults in the electric powertrains. The proposed method is based on pattern recognition using convolutional neural network to detect effectively not only single faults at constant speed but also multiple faults in variable speed operations. The effectiveness of the proposed method is validated via an in-house experimental setup.
Ullah, N., Ali, S. M., Khan, B., Mehmood, C. A., Anwar, S. M., Majid, M., Farid, U., Nawaz, M. A., Ullah, Z..  2019.  Energy Efficiency: Digital Signal Processing Interactions Within Smart Grid. 2019 International Conference on Engineering and Emerging Technologies (ICEET). :1–6.
Smart Grid (SG) is regarded as complex electrical power system due to massive penetration of Renewable Energy Resources and Distribution Generations. The implementation of adjustable speed drives, advance power electronic devices, and electric arc furnaces are incorporated in SG (the transition from conventional power system). Moreover, SG is an advance, automated, controlled, efficient, digital, and intelligent system that ensures pertinent benefits, such as: (a) consumer empowerment, (b) advanced communication infrastructure, (c) user-friendly system, and (d) supports bi-directional power flow. Digital Signal Processing (DSP) is key tool for SG deployment and provides key solutions to a vast array of complex SG challenges. This research provides a comprehensive study on DSP interactions within SG. The prominent challenges posed by conventional grid, such as: (a) monitoring and control, (b) Electric Vehicles infrastructure, (c) cyber data injection attack, (d) Demand Response management and (e) cyber data injection attack are thoroughly investigated in this research.
Niddodi, Chaitra, Lin, Shanny, Mohan, Sibin, Zhu, Hao.  2019.  Secure Integration of Electric Vehicles with the Power Grid. 2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm). :1–7.
This paper focuses on the secure integration of distributed energy resources (DERs), especially pluggable electric vehicles (EVs), with the power grid. We consider the vehicle-to-grid (V2G) system where EVs are connected to the power grid through an `aggregator' In this paper, we propose a novel Cyber-Physical Anomaly Detection Engine that monitors system behavior and detects anomalies almost instantaneously (worst case inspection time for a packet is 0.165 seconds1). This detection engine ensures that the critical power grid component (viz., aggregator) remains secure by monitoring (a) cyber messages for various state changes and data constraints along with (b) power data on the V2G cyber network using power measurements from sensors on the physical/power distribution network. Since the V2G system is time-sensitive, the anomaly detection engine also monitors the timing requirements of the protocol messages to enhance the safety of the aggregator. To the best of our knowledge, this is the first piece of work that combines (a) the EV charging/discharging protocols, the (b) cyber network and (c) power measurements from physical network to detect intrusions in the EV to power grid system.1Minimum latency on V2G network is 2 seconds.
Shah, Saurabh, Murali, Meera, Gandhi, Priyanka.  2019.  Platform Software Development for Battery Management System in Electric Vehicle. 2019 IEEE International Conference on Sustainable Energy Technologies and Systems (ICSETS). :262–267.

The use of green energy is becoming increasingly more important in today's world. Therefore, the use of electric vehicles (EVs) is proving to be the best choice for the environment in terms of public and personal transportation. As the electric vehicles are battery powered, their management becomes very important because using batteries beyond their safe operating area can be dangerous for the entire vehicle and the person onboard. To maintain the safety and reliability of the battery, it is necessary to implement the functionalities of continuous cell monitoring and evaluation, charge control and cell balancing in battery management systems (BMS). This paper presents the development of platform software required for the implementation of these functionalities. This platform is based on a digital signal processing platform which is a master-slave structure. Serial communication technology is adopted between master and slave. This system allows easier controllability and expandability.

Ohata, Keita, Adachi, Masakazu, Kusaka, Keisuke, Itoh, Jun-Ichi.  2019.  Three-phase AC-DC Converter for EV Rapid Charging with Wireless Communication for Decentralized Controller. 2019 10th International Conference on Power Electronics and ECCE Asia (ICPE 2019 - ECCE Asia). :3033–3039.

This paper proposes a multi-modular AC-DC converter system using wireless communication for a rapid charger of electric vehicles (EVs). The multi-modular topology, which consists of multiple modules, has an advantage on the expandability regarding voltage and power. In the proposed system, the input current and output voltage are controlled by each decentralized controller, which wirelessly communicates to the main controller, on each module. Thus, high-speed communication between the main and modules is not required. As the results in a reduced number of signal lines. The fundamental effectiveness of the proposed system is verified with a 3-kW prototype. In the experimented results, the input current imbalance rate is reduced from 49.4% to 0.1%, where total harmonic distortion is less than 3%.

Zhong, Q., Blaabjerg, F., Cecati, C..  2017.  Power-Electronics-Enabled Autonomous Power Systems. IEEE Transactions on Industrial Electronics. 64:5904–5906.

The eleven papers in this special section focus on power electronics-enabled autonomous systems. Power systems are going through a paradigm change from centralized generation to distributed generation and further onto smart grid. Millions of relatively small distributed energy resources (DER), including wind turbines, solar panels, electric vehicles and energy storage systems, and flexible loads are being integrated into power systems through power electronic converters. This imposes great challenges to the stability, scalability, reliability, security, and resiliency of future power systems. This section joins the forces of the communities of control/systems theory, power electronics, and power systems to address various emerging issues of power-electronics-enabled autonomous power systems, paving the way for large-scale deployment of DERs and flexible loads.

Choucri, N., Agarwal, G..  2017.  Analytics for Smart Grid Cybersecurity. 2017 IEEE International Symposium on Technologies for Homeland Security (HST). :1–3.

Guidelines, directives, and policy statements are usually presented in ``linear'' text form - word after word, page after page. However necessary, this practice impedes full understanding, obscures feedback dynamics, hides mutual dependencies and cascading effects and the like, - even when augmented with tables and diagrams. The net result is often a checklist response as an end in itself. All this creates barriers to intended realization of guidelines and undermines potential effectiveness. We present a solution strategy using text as ``data'', transforming text into a structured model, and generate a network views of the text(s), that we then can use for vulnerability mapping, risk assessments and control point analysis. We apply this approach using two NIST reports on cybersecurity of smart grid, more than 600 pages of text. Here we provide a synopsis of approach, methods, and tools. (Elsewhere we consider (a) system-wide level, (b) aviation e-landscape, (c) electric vehicles, and (d) SCADA for smart grid).

Zhang, Q., Ma, Z., Li, G., Qian, Z., Guo, X..  2016.  Temperature-dependent demagnetization nonlinear Wiener model with neural network for PM synchronous machines in electric vehicle. 2016 19th International Conference on Electrical Machines and Systems (ICEMS). :1–4.

The inevitable temperature raise leads to the demagnetization of permanent magnet synchronous motor (PMSM), that is undesirable in the application of electrical vehicle. This paper presents a nonlinear demagnetization model taking into account temperature with the Wiener structure and neural network characteristics. The remanence and intrinsic coercivity are chosen as intermediate variables, thus the relationship between motor temperature and maximal permanent magnet flux is described by the proposed neural Wiener model. Simulation and experimental results demonstrate the precision of temperature dependent demagnetization model. This work makes the basis of temperature compensation for the output torque from PMSM.

Tianyu Zhao, Chang Chen, Lingbo Wei, Mengke Yu.  2014.  An anonymous payment system to protect the privacy of electric vehicles. Wireless Communications and Signal Processing (WCSP), 2014 Sixth International Conference on. :1-6.

Electric vehicle is the automobile that powered by electrical energy stored in batteries. Due to the frequent recharging, vehicles need to be connected to the recharging infrastructure while they are parked. This may disclose drivers' privacy, such as their location that drivers may want to keep secret. In this paper, we propose a scheme to enhance the privacy of the drivers using anonymous credential technique and Trusted Platform Module(TPM). We use anonymous credential technique to achieve the anonymity of vehicles such that drivers can anonymously and unlinkably recharge their vehicles. We add some attributes to the credential such as the type of the battery in the vehicle in case that the prices of different batteries are different. We use TPM to omit a blacklist such that the company that offer the recharging service(Energy Provider Company, EPC) does not need to conduct a double spending detection.

Zhuoping Yu, Junxian Wu, Lu Xiong.  2014.  Research of stability control of distributed drive electric vehicles under motor failure modes. Transportation Electrification Asia-Pacific (ITEC Asia-Pacific), 2014 IEEE Conference and Expo. :1-5.

With the application and promotion of electric vehicles, vehicle security problems caused by actuator reliability have become increasingly prominent. Firstly, the paper analyses and sums motor failure modes and their effects of permanent magnet synchronous motor (PMSM) , which is commonly used on electric vehicles. And then design a hierarchical structure of the vehicle control strategies and the corresponding algorithms, and adjust based on the different failure modes. Finally conduct simulation conditions in CarSim environment. Verify the control strategy and algorithm can maintain vehicle stability and reduce the burden on driver under motor failure conditions.