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Heat Pumps for BEVs: Architectures and Performance Analysis

Centro Ricerche Fiat SCpA-Walter Ferraris, Federica Bettoja, Mauro Casella, Matteo Rostagno, Angela Tancredi
  • Technical Paper
  • 2020-37-0030
To be published on 2020-06-23 by SAE International in United States
Electric vehicles have never been more popular, yet fears around being left stranded by an exhausted battery remain a key reason why some car buyers resist making a purchase. Bigger batteries are not always the solution because of the direct link with higher costs and high impact on weight. A re-engineering of the most energy-consuming auxiliaries is mandatory and the thermal management function is on top of the redesign request list. Heat Pump solution is considered one of the best way to save energy and reduce the impact on vehicle range of heating and cooling function, but the automotive application requires a careful definition of the system features to avoid unjustified growing up of complexity as well as an unneeded system over-sizing. The paper aims to give an overview on the heat pump design best practices through a virtual performance comparison of different lay-out configurations, which have been selected starting from a benchmark analysis crossed with a detailed vehicle segment-oriented functions selection. Control strategies role, costs, and target requirements have been used as drivers for…
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Time Domain Full Vehicle Interior Noise Calculation from Component Level Data by Machine Learning

Mercedes-Benz AG-Dimitrios Ernst Tsokaktsidis, Clemens Nau
Technical University of Munich-Steffen Marburg
  • Technical Paper
  • 2020-01-1564
To be published on 2020-06-03 by SAE International in United States
Computational models directly derived from data gained increased interest in recent years. Data-driven approaches have brought breakthroughs in different research areas such as image-, video- and audio-processing. Often denoted as Machine Learning (ML), these approaches are not widely applied in the field of vehicle Noise, Vibration and Harshness (NVH) yet. Related works mainly discuss the topic with respect to structural health monitoring, psychoacoustics, traffic noise and as improvement to existing numerical simulation methods. Vehicle interior noise is a major quality criterion for today’s automotive development. To estimate noise levels early in the development process, deterministic system descriptions are created by utilizing time-consuming measurement techniques. This paper examines whether pattern-recognizing algorithms are suitable to improve the prediction process for a steering system. Starting from operational measurements, a procedure to calculate the sound pressure level in the passenger cabin is developed and investigated. Component time domain data serves as basis for the computation. The important inputs are determined by a correlation analysis. Input selection is followed by data reduction. After preprocessing, a supervised learning environment is established.…
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Cooperative Mandatory Lane Change for Connected Vehicles on Signalized Intersection Roads

Clemson University-Zhiyuan Du, Bin Xu, Pierluigi Pisu
  • Technical Paper
  • 2020-01-0889
To be published on 2020-04-14 by SAE International in United States
This paper presents a hierarchical control architecture to coordinate a group of connected vehicles on signalized intersection roads, where vehicles are allowed to change lane to follow a prescribed path. The proposed hierarchical control strategy consists of two control levels: a high level controller at the intersection and a decentralized low level controller in each car. In the hierarchical control architecture, the centralized intersection controller estimates the target velocity for each approaching connected vehicle to avoid red light stop based on the signal phase and timing (SPAT) information. Each connected vehicle as a decentralized controller utilizes model predictive control (MPC) to track the target velocity in a fuel efficient manner. The main objective in this paper is to consider mandatory lane changes. As in the realistic scenarios, vehicles are not required to drive in single lane. More specifically, they more likely change their lanes prior to signals. Hence, the vehicle decentralized controllers must prepare to cooperate with the vehicle that has a mandatory lane change request (host vehicle). The cooperative mandatory lane change is accomplished…
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Leveraging real-world driving data sets for design and impact evaluation of energy efficient control strategies.

General Motors LLC-Bharatkumar Hegde, Steven E. Muldoon
National Renewable Energy Laboratory-Michael O'Keefe, Jeffrey Gonder
  • Technical Paper
  • 2020-01-0585
To be published on 2020-04-14 by SAE International in United States
Modeling and simulation are crucial in the development of advanced energy efficient control strategies. Utilizing real-world driving data as the underlying basis for control design and simulation lends veracity to projected real-world energy savings. Standardized drive cycles are limited in their utility for evaluating advanced driving strategies that utilize connectivity and on-vehicle sensing, primarily because they are non-causal and are typically intended for evaluating emission and fuel economy under controlled conditions. Real-world driving data, because of its scale, is a useful representation of various road types, driving styles, and driving environments. The scale of real-world data also presents challenges in effectively using it in simulations. A fast and efficient simulation methodology is necessary to handle the large number of simulations performed for design analysis and impact evaluation of control strategies. In this study, we present two methods of leveraging real-world data in both design optimization of energy efficient control strategies and in evaluating the real-world impact of those control strategies upon large-scale deployment. Through these methodologies, strategies with highest impact on energy savings were selected…
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Vision system for detecting a small object with arbitrary shape at far range

Great Wall Motor Co., Ltd.-Shunji Miyahara, Huan Li, Kunpeng Xie, Jincheng Bai
  • Technical Paper
  • 2020-01-0094
To be published on 2020-04-14 by SAE International in United States
As one of the advanced sensing technologies of the autonomous driving, we have been working on the new vision system. It focuses on detecting the small object at far ranges. It enables to detour a vehicle by avoiding small object. This system is based on the high-resolution mono-camera with narrow FOV and the algorithms for object-detection and lane-detection. Since we have developed the system for the traffic cones, we proceed to the algorithm for an unknown object with arbitrary shape. It can detect the object and estimate its range by using the information of lane detection even though the shape of the object is unknown. Here the system architecture and how to make the detection and the ranging of unknown objects are described. Some test result are also described.
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Evaluation Methodologies in the Development of Dynamically Reconfigurable Systems in the Automotive Industry

BMW Group-Florian Oszwald, Ruben Bertelo
Karlsruhe Institute Of Technology-Juergen Becker
  • Technical Paper
  • 2020-01-1363
To be published on 2020-04-14 by SAE International in United States
Classical decentralized architectures based on large networks of microprocessor-based Electronic Control Units (ECU), namely those used in self-driving cars and other highly-automated applications used in the automotive industry, are becoming more and more complex. These new, high computational power demand applications are constrained by limits on energy consumption, weight, and size of the embedded components. The adoption of new embedded centralized electrical/electronic (E/E) architectures based on dynamically reconfigurable hardware represents a new possibility to tackle these challenges. However, they also raise concerns and questions about their safety. Hence, an appropriate evaluation must be performed to guarantee that safety requirements resulting from an Automotive Safety Integrity Level (ASIL) according to the standard ISO 26262 are met.In this paper, a methodology for the evaluation of dynamically reconfigurable systems based on centralized architectures is presented. The aim is to evaluate the reliability and probability of failure while exploring the design space without compromise the overall system performance.The methodology is divided into three stages. In the first stage, the system is decomposed, and its sub-systems are isolated before applying…
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ROBUST SENSOR FUSED OBJECT DETECTION USING CONVOLUTIONAL NEURAL NETWORKS FOR AUTONOMOUS VEHICLES

Kettering University-Jungme Park, Sriram Jayachandran Raguraman, Aakif Aslam, Shruti Gotadki
  • Technical Paper
  • 2020-01-0100
To be published on 2020-04-14 by SAE International in United States
Nowadays, the proliferation of research on the autonomous vehicles and the Advanced Driver Assistance System (ADAS) has resulted from the need for intelligent and safer mobility. Environmental perception is considered as an essential module for autonomous driving and ADAS. In the object detection problem, deep Convolutional Neural Networks (CNNs) become the State-of-the-Art with various different architectures. However, the performances of the existing CNNs have dropped when detecting small objects in distance. To deploy the environmental perception system in real world applications, it is important that the perception system achieves the high accuracy regardless the obstacle sizes, the distances, and weather conditions. In this paper, a sensor fused system for object detection, tracking and classification is proposed by utilizing the advantages of both vision sensor and automotive radar sensor. Data from on-vehicle radar sensor and camera sensor are processed in real time simultaneously. The proposed system consists of three modules: 1) the Coordinate Conversion module converts the radar coordinates into the image coordinate system. 2) Multi Level-Multi Region detection system based on the deep CNNs. The…
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Vehicle Design Considerations Enabling High-Performance Charging

Magna Steyr Fahrzeugtechnik AG & Co. KG-Christian Josef Paar, Helmut Martin Waser, Heimo Kreimaier, Inés Cuenca-Jaen, Florian Eibler
  • Technical Paper
  • 2020-01-1440
To be published on 2020-04-14 by SAE International in United States
Customer requirements such as range anxiety are the driver for increasing the charging power of battery-electric vehicles. High-performance charging theoretically enables time targets of faster than 30 kilometers (19 miles) recharging per minute. Due to physical limitations (i.e., current limits of the components available) a charging power of greater than 200 kilowatt arises the question of the voltage level required to fulfill the power demand. One possible approach to achieve high charging power is increasing the battery voltage, i.e., increasing the voltage level from 400 V to 800 V is one simple measure. This publication discusses the main aspects of charging by incorporating all high-voltage components in the vehicle. An increase of the voltage level and charging power affects all high-voltage components, especially the thermal management of the battery needs special consideration. High-voltage vehicle architecture design considerations are discussed including thermal-management and battery-design aspects. Different charging curves from existing vehicles are compared with a generic fast charging profile which is defined using theoretical background of available cells including consideration of physical and chemical limits (e.g.,…
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An Evaluation of Future Topologies and Architectures for Highly Reliable Electrical Distribution Systems

University of Kassel-Ludwig Brabetz, Mohamed Ayeb, Janis Lehmann, Benjamin Löwer
  • Technical Paper
  • 2020-01-1296
To be published on 2020-04-14 by SAE International in United States
Within the scope of the development of autonomous vehicles, the continuous introduction of automated driving functions considerably increases the mandatory reliability requirements of the electrical power supply, and consequently of the electrical distribution system (EDS). In addition, the overall rising number of electrical functions in future vehicles leads to significantly higher electrical power demands, while strict cost, weight and packaging constraints must be upheld. Current developments focus mostly on the improvement of the conventional EDS, e.g. by adding redundancies, enhancing physical robustness, or redimensioning critical components. New approaches address predictive power management, better diagnostic capabilities, and, the subject of this paper, new topologies and architectures. Alternative topologies are derivations of the conventional tree structure, as well as ring- or linear-bus-based zonal architectures, which feature in part distributed storage devices or semiconductor switches that rearrange the power paths in case of a fault. The presented approach is a method for both the systematical description of EDS topologies and architectures, and the assessment of their reliability. It is based on a data model designed for a simple…
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Joint Calibration of Dual LiDARs and Camera Using a Circular Chessboard

Tongji University-Zhenwen Deng, Lu Xiong, Dong Yin, Fengwu Shan
  • Technical Paper
  • 2020-01-0098
To be published on 2020-04-14 by SAE International in United States
Environmental perception is a crucial subsystem in autonomous vehicles. In order to build safe and efficient traffic transportation, several researches have been proposed to build accurate, robust and real-time perception systems. Camera and LiDAR are widely equipped on autonomous self-driving cars and developed with many algorithms in recent years. The fusion system of camera and LiDAR provides state-of the-art methods for environmental perception due to the defects of single vehicular sensor. Extrinsic parameter calibration is able to align the coordinate systems of sensors and has been drawing enormous attention. However, differ from spatial alignment of two sensors’ data, joint calibration of multi-sensors (more than two sensors) should balance the degree of alignment between each two sensors. In this paper, we assemble a test platform which is made up of dual LiDARs and one monocular camera and use the same sensing hardware architecture as intelligent sweeper designed by our laboratory. Meanwhile, we propose the related joint calibration method using a circular chessboard. The center of circular chessboard is respectively detected in camera image to get pixel…