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A Comprehensive Data Reduction Algorithm for Automotive Multiplexing

SAE International Journal of Passenger Cars - Electronic and Electrical Systems

University of Ottawa, Canada-Aliakbar A. Baldiwala, Dan Necsulescu
  • Journal Article
  • 07-12-01-0002
Published 2019-04-08 by SAE International in United States
Present-day vehicles come with a variety of new features like the pre-crash warning, the vehicle-to-vehicle communication, semi-autonomous driving systems, telematics, drive by wire. They demand very high bandwidth from in-vehicle networks. Various ECUs present inside the automotive transmits useful information via automotive multiplexing. Transmission of data in real-time achieves optimum functionality. The high bandwidth and high-speed requirement can be achieved either by using multiple buses or by implementing higher bandwidth. But, by doing so, the cost of the network as well as the complexity of the wiring increases. Another option is to implement higher layer protocol which can reduce the amount of data transferred by using data reduction (DR) techniques, thus reducing the bandwidth usage. The implementation cost is minimal as the changes are required in the software only and not in hardware. This article presents a new data reduction algorithm termed as “Comprehensive Data Reduction (CDR)” algorithm. The article also demonstrates a comparison of the proposed algorithm with the boundary of fifteen compression algorithms and compression area selection algorithms. The results show that the…
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An Adaptive Neuro-Fuzzy Inference System (ANFIS) Based Model for the Temperature Prediction of Lithium-Ion Power Batteries

SAE International Journal of Passenger Cars - Electronic and Electrical Systems

China Automotive Technology and Research Center Co., Ltd. (CATARC)-Bin Fan, Chunjing Lin, Fang Wang, Shiqiang Liu, Lei Liu
Tongji University-Sichuan Xu
  • Journal Article
  • 07-12-01-0001
Published 2018-08-14 by SAE International in United States
Li-ion batteries have been widely applied in the areas of personal electronic devices, stationary energy storage system and electric vehicles due to their high energy/power density, low self-discharge rate and long cycle life etc. For the better designs of both the battery cells and their thermal management systems, various numerical approaches have been proposed to investigate the thermal performance of power batteries. Without the requirement of detailed physical and thermal parameters of batteries, this article proposed a data-driven model using the adaptive neuro-fuzzy inference system (ANFIS) to predict the battery temperature with the inputs of ambient temperature, current and state of charge. Thermal response of a Li-ion battery module was experimentally evaluated under various conditions (i.e. ambient temperature of 0, 5, 10, 15 and 20 °C, and current rate of C/2, 1C and 2C) to acquire the necessary data sets for model development and validation. A Sugeno-type ANFIS model was tuned using the obtained data. The numbers of input membership functions (MFs) representing the three input parameters of this model are 1, 2, 3, respectively.…
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Cyberattacks and Countermeasures for Intelligent and Connected Vehicles

SAE International Journal of Passenger Cars - Electronic and Electrical Systems

Tongji University, China-Feng Luo, Shuo Hou
  • Journal Article
  • 07-12-01-0005
Published 2019-10-14 by SAE International in United States
ICVs are expected to make the transportation safer, cleaner, and more comfortable in the near future. However, the trend of connectivity has greatly increased the attack surfaces of vehicles, which makes in-vehicle networks more vulnerable to cyberattacks which then causes serious security and safety issues. In this article, we therefore systematically analyzed cyberattacks and corresponding countermeasures for in-vehicle networks of intelligent and connected vehicles (ICVs). Firstly, we analyzed the security risk of ICVs and proposed an in-vehicle network model from a hierarchical point of view. Then, we discussed possible cyberattacks at each layer of proposed network model. After that, we provided an overview of the state of the art of the potential countermeasures against cyberattacks, such as secure hardware architecture, encryption and authentication, network firewall, intrusion detection system, and secure Firmware over the air (FOTA), and then a reasonable defense mechanism is proposed. At last, some challenges and future works related to cyberattacks against ICVs were discussed. This article aims to review the cyberattacks for ICVs and suggest comprehensive security countermeasures.
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Energy-Management Strategy for Four-Wheel Drive Electrohydraulic Hybrid System with Optimal Comprehensive Efficiency

SAE International Journal of Passenger Cars - Electronic and Electrical Systems

Chongqing University, China-Yang Yang, Ke Lu, Chunyun Fu
  • Journal Article
  • 07-12-01-0004
Published 2019-08-22 by SAE International in United States
The four-wheel drive electric sport utility vehicle (SUV) requires high dynamic performance, and the front and rear axles are matched with a high-power motor. High-power motors operate under low-speed and low-torque conditions, with low efficiency and large power loss. To reduce the power loss under low-speed and low-load conditions, a hybrid system of front and rear dual motors and dual hydraulic pumps/motors is designed. A simulation model of a four-wheel drive SUV electrohydraulic hybrid system is constructed. Aiming at the optimal energy consumption, a dynamic programming algorithm is adopted to establish the driving control rules of the vehicle. Constrained by the Economic Commission for Europe Regulation No.13 (ECE R13), a braking-force distribution strategy for the front and rear axles is formulated. On the premise of satisfying the braking safety, regenerative braking is preferred, and the braking energy is recovered to the greatest extent possible. The optimal efficiency curve of the motor is identified, and an energy-management strategy based on the optimal efficiency curve of the motor is established. The comprehensive efficiency of the dual motor…
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A Maneuver-Based Threat Assessment Strategy for Collision Avoidance

SAE International Journal of Passenger Cars - Electronic and Electrical Systems

Beihang University, China-Weiwen Deng
General Motors LLC, USA-Jinsong Wang
  • Journal Article
  • 07-12-01-0003
Published 2019-08-22 by SAE International in United States
Advanced driver-assistance systems (ADAS) are being developed for more and more complicated application scenarios, which often require more predictive strategies with better understanding of the driving environment. Taking traffic vehicles’ maneuvers into account can greatly expand the beforehand time span for danger awareness. This article presents a maneuver-based strategy to vehicle collision threat assessment. First, a maneuver-based trajectory prediction model (MTPM) is built, in which near-future trajectories of ego vehicle and traffic vehicles are estimated with the combination of vehicle’s maneuvers and kinematic models that correspond to every maneuver. The most probable maneuvers of ego vehicle and each traffic vehicles are modelled and inferred via Hidden Markov Models with mixture of Gaussians outputs (GMHMM). Based on the inferred maneuvers, trajectory sets consisting of vehicles’ position and motion states are predicted by kinematic models. Subsequently, time to collision (TTC) is calculated in a strategy of employing collision detection at every predicted trajectory instance. For this purpose, safe areas via bounding boxes are applied on every vehicle, and Separating Axis Theorem (SAT) is applied for collision prediction…
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