Electric Vehicles Charging Control based on Future Internet Generic Enablers

In this paper a rationale for the deployment of Future Internet based applications in the field of Electric Vehicles (EVs) smart charging is presented. The focus is on the Connected Device Interface (CDI) Generic Enabler (GE) and the Network Information and Controller (NetIC) GE, which are recognized to have a potential impact on the charging control problem and the configuration of communications networks within reconfigurable clusters of charging points. The CDI GE can be used for capturing the driver feedback in terms of Quality of Experience (QoE) in those situations where the charging power is abruptly limited as a consequence of short term grid needs, like the shedding action asked by the Transmission System Operator to the Distribution System Operator aimed at clearing networks contingencies due to the loss of a transmission line or large wind power fluctuations. The NetIC GE can be used when a master Electric Vehicle Supply Equipment (EVSE) hosts the Load Area Controller, responsible for managing simultaneous charging sessions within a given Load Area (LA); the reconfiguration of distribution grid topology results in shift of EVSEs among LAs, then reallocation of slave EVSEs is needed. Involved actors, equipment, communications and processes are identified through the standardized framework provided by the Smart Grid Architecture Model (SGAM).Comment: To appear in IEEE International Electric Vehicle Conference (IEEE IEVC 2014

Determining vehicle acceleration from noisy non-uniformly sampled speed data for control purposes

International audienceVehicle acceleration is an important variable for many automotive control applications. In this paper, we present an approach to estimate vehicle acceleration from vehicle speed data coming from the CAN (Controller Area Network) bus. The proposed method, which can be seen as an extension of the Savitzky-Golay filter to non-uniformly sampled signals, re-samples them to a constant period while filtering noise coming from different sources and also provides a proper estimation of vehicle acceleration. We also consider the frequency response of the filtering effect of the method. Finally, some practical considerations for efficient implementation of the algorithm are given

Integration of UAVS with Real Time Operating Systems and Establishing a Secure Data Transmission

Indiana University-Purdue University Indianapolis (IUPUI)In today’s world, the applications of Unmanned Aerial Vehicle (UAV) systems are leaping by extending their scope from military applications on to commercial and medical sectors as well. Owing to this commercialization, the need to append external hardware with UAV systems becomes inevitable. This external hardware could aid in enabling wireless data transfer between the UAV system and remote Wireless Sensor Networks (WSN) using low powered architecture like Thread, BLE (Bluetooth Low Energy). The data is being transmitted from the flight controller to the ground control station using a MAVlink (Micro Air Vehicle Link) protocol. But this radio transmission method is not secure, which may lead to data leakage problems. The ideal aim of this research is to address the issues of integrating different hardware with the flight controller of the UAV system using a light-weight protocol called UAVCAN (Unmanned Aerial Vehicle Controller Area Network). This would result in reduced wiring and would harness the problem of integrating multiple systems to UAV. At the same time, data security is addressed by deploying an encryption chip into the UAV system to encrypt the data transfer using ECC (Elliptic curve cryptography) and transmitting it to cloud platforms instead of radio transmission

Ethernet Over Plastic Optical Fiber for Use in the Control System Network for Automotive Applications

Plastic optical fiber (POF) for use in automotive applications is not a new concept and has been used in some vehicles for infotainment media distribution within the Media Oriented Systems Transport protocol. However, the use of POF for the control network’s physical layer is a concept that has not been implemented in automotive applications. Many aspects of a vehicle can be improved by implementing POF as the physical backbone for the control network. Currently, the Controller Area Network (CAN) is used as the primary backbone control network protocol for most automobiles as it is inexpensive and reliable. However, CAN is limited to 500 kbps in most vehicles and is easily accessible. Ethernet may provide the improvements of speed and security needed in today’s feature rich and connected vehicles. The feasibility of implementing Ethernet over POF as the control network for automotive applications is the topic of this research investigation

Kalman and particle filtering methods for full vehicle and tyre identification

This paper considers identification of all significant vehicle handling dynamics of a test vehicle, including identification of a combined-slip tyre model, using only those sensors currently available on most vehicle controller area network buses. Using an appropriately simple but efficient model structure, all of the independent parameters are found from test vehicle data, with the resulting model accuracy demonstrated on independent validation data. The paper extends previous work on augmented Kalman Filter state estimators to concentrate wholly on parameter identification. It also serves as a review of three alternative filtering methods; identifying forms of the unscented Kalman filter, extended Kalman filter and particle filter are proposed and compared for effectiveness, complexity and computational efficiency. All three filters are suited to applications of system identification and the Kalman Filters can also operate in real-time in on-line model predictive controllers or estimators

Soft-Defined Heterogeneous Vehicular Network: Architecture and Challenges

Heterogeneous Vehicular NETworks (HetVNETs) can meet various quality-of-service (QoS) requirements for intelligent transport system (ITS) services by integrating different access networks coherently. However, the current network architecture for HetVNET cannot efficiently deal with the increasing demands of rapidly changing network landscape. Thanks to the centralization and flexibility of the cloud radio access network (Cloud-RAN), soft-defined networking (SDN) can conveniently be applied to support the dynamic nature of future HetVNET functions and various applications while reducing the operating costs. In this paper, we first propose the multi-layer Cloud RAN architecture for implementing the new network, where the multi-domain resources can be exploited as needed for vehicle users. Then, the high-level design of soft-defined HetVNET is presented in detail. Finally, we briefly discuss key challenges and solutions for this new network, corroborating its feasibility in the emerging fifth-generation (5G) era

A Learning-based Stochastic MPC Design for Cooperative Adaptive Cruise Control to Handle Interfering Vehicles

Vehicle to Vehicle (V2V) communication has a great potential to improve reaction accuracy of different driver assistance systems in critical driving situations. Cooperative Adaptive Cruise Control (CACC), which is an automated application, provides drivers with extra benefits such as traffic throughput maximization and collision avoidance. CACC systems must be designed in a way that are sufficiently robust against all special maneuvers such as cutting-into the CACC platoons by interfering vehicles or hard braking by leading cars. To address this problem, a Neural- Network (NN)-based cut-in detection and trajectory prediction scheme is proposed in the first part of this paper. Next, a probabilistic framework is developed in which the cut-in probability is calculated based on the output of the mentioned cut-in prediction block. Finally, a specific Stochastic Model Predictive Controller (SMPC) is designed which incorporates this cut-in probability to enhance its reaction against the detected dangerous cut-in maneuver. The overall system is implemented and its performance is evaluated using realistic driving scenarios from Safety Pilot Model Deployment (SPMD).Comment: 10 pages, Submitted as a journal paper at T-I