Your Selections

Big data
Show Only


File Formats

Content Types









   This content is not included in your SAE MOBILUS subscription, or you are not logged in.

Eco-Vehicle Battery System Big-Data Analysis and Fault Mode and Fault Tree Analysis (FTA) Related Robust System Development

Hyundai Motor Company-Jeong-Hun Seo, Yong Jae Kim, Woo Jin Shin, Hee Yae Yang, Yuseok Kim, Kang Ju Cha, Mi Seon Kim
  • Technical Paper
  • 2020-01-0447
To be published on 2020-04-14 by SAE International in United States
High-voltage battery system plays a critical role in eco-friendly vehicles due to its effect on the cost and the electric driving range of eco-friendly vehicles. In order to secure the customer pool and the competitiveness of eco-vehicle technology, vehicle electrification requires lowering the battery cost and satisfying the customer needs when driving the vehicles in the real roads, for example, maximizing powers for fun drive, increasing battery capacities for achieving appropriate trip distances, etc. Because these vehicle specifications have a critical effect on the high-voltage battery specification, the key technology of the vehicle electrification is the appropriate decision on the specification of the high-voltage battery system, such as battery capacity and power. These factors affect the size of battery system and vehicle under floor design and also the profitability of the eco-friendly vehicles. In this work, the big data of Sonata hybrid electric vehicle (HEV)/plug-in hybrid electric vehicle (PHEV) battery system has been analyzed in term of four categories: cell, thermal management, 12 volt battery, and power electronics part. Analysis results show that the ratio…
   This content is not included in your SAE MOBILUS subscription, or you are not logged in.

Using Polygot Persistence with NoSQL Databases for Streaming Multimedia, Sensor, and Messaging Services in Autonomous Vehicles

Wayne State University-Kyle W. Brown
  • Technical Paper
  • 2020-01-0942
To be published on 2020-04-14 by SAE International in United States
The explosion of big data has created challenges for both cloud-based systems and Autonomous Vehicles (AVs) in data collection and management. The same challenges are now being realized in developing databases for integrated sensors, streaming, real-time and on-demand services in AVs. With just one AV expecting to generate over 30 Terabytes of data a day, modern NoSQL databases provide opportunities to horizontally scale AV data seamlessly. NoSQL provides solutions designed to accommodate a wide variety of data models such as, key-value, document, column and graph databases. Key-value stores are by nature scalable, fast processing, and distribute horizontally. These databases are tasked with handling several data types including IoT, radar, lidar, ultra-sonic sensors, GPS, odometry, and sensor data while providing streaming and real-time services. NoSQL can store and utilize structured, semi-structured, and unstructured data necessary for multimedia storage needs. NoSQL databases such as Graph databases support big data necessary for the demands of modern software development. Graph databases can scale AV data by using geospatial and geolocation coordinates as entities for flexible queries and pattern recognition.…
   This content is not included in your SAE MOBILUS subscription, or you are not logged in.

Coasting Technology for Real-World Fuel Economy Improvementof a Hybrid Vehicle

Toyota Motor Corporation-Tomoya Yamaguchi
  • Technical Paper
  • 2020-01-1195
To be published on 2020-04-14 by SAE International in United States
Automobile manufactures need to adopt new technologies to meet global CO2 (carbon dioxide) emission regulations and better fuel efficiency demands from customers. Also, the production cost should be as low as possible for an affordable vehicle. Therefore, it is advantageous for OEMs to develop fuel efficient technologies which can be controlled by software without additional hardware costs. The coasting control is a fuel efficiency improvement technology that can be implemented by the change of vehicle software only. The coasting control is a technology that reduces the driving resistance (Deceleration) when the driver releases the gas pedal. This technology leads to reducing the energy required for the vehicle to drive and results in improving the real-world fuel economy. In an internal combustion engine (ICE) vehicle, the coasting state is achieved by changing the gear to neutral, and the effect has been discussed and clarified by many previous studies. On the other hand, in the coasting state of a hybrid vehicle, the regenerative energy to the motor is reduced while the driver releases the gas pedal. The…
   This content is not included in your SAE MOBILUS subscription, or you are not logged in.

Research on the Test and Evaluation Method of Fuel Consumption Based on Chinese Light-duty Test Cycle

China Automotive Technology and Research-Yang Wang, Chun Hui, Yu Liu
  • Technical Paper
  • 2020-01-0363
To be published on 2020-04-14 by SAE International in United States
Considering the defect of current test method and learning from the experience of methods developing around the world, a method adopted China Light-duty Vehicle Test Cycle (CLTC) which is suitable for the real condition of Chinese road comes up based on three factors. Through the test results of 20 vehicles and big data statistics, the results obtained by this method are close to those from customers which the difference between them is around 6%. Thus, this method can evaluate the real fuel consumption of vehicle running on Chinese road. Furthermore, the rationality of this method is proved.
   This content is not included in your SAE MOBILUS subscription, or you are not logged in.


Centro Universitario da FEI-Renato Ferreira Junior, Dra. Gabriela Scur
  • Technical Paper
  • 2019-36-0093
Published 2020-01-13 by SAE International in United States
With the increase in the use of information technology and communication, Internet of Things, Big Data, in addition to the concepts of sustainability, a new strategy has been structured, which aims to add value to the traditional PSS model, in the integration of new services to products. The challenge is how to change the current business model of a fully product-oriented (PO) company into a supplier of products with integrated services, in a new business model. From the theoretical propositions and best practices of companies that have implemented PSS businesses models, this paper propose and validate a systematization of strategic actions that make possible for product-oriented companies to change to a new PSS business model, and can be used as a guideline to the PSS implementation, as it compiles the key aspects needed for each strategic area, the important actions found in the literature and bibliographic references that may help in further research. In terms of theoretical relevance, this paper expands the PSS model, using the Big Data to generate new business. Managerial contribution was…
This content contains downloadable datasets
Annotation ability available
   This content is not included in your SAE MOBILUS subscription, or you are not logged in.

Unsettled Topics Concerning the Field Testing of Automated Driving Systems

Bob McQueen and Associates-Bob McQueen
  • Research Report
  • EPR2019009
Published 2019-12-19 by SAE International in United States
Automated driving systems (ADS) have the potential to revolutionize transportation. Through the automation of driver functions in the application of advanced technology within the vehicle, significant improvements can be made to safety, efficiency, user experience, and the preservation of the environment. According to the US Department of Transportation [1], there are more than 1,400 cars, trucks, buses, and other vehicles being tested by more than 80 companies across the USA. Implementation of ADS technology is well advanced, with many sites across the USA incorporating automated vehicles (AVs) into wider programs to apply advanced technology to transportation. Discussions with the public sector’s implementing agencies suggest that one of the barriers to faster progress lies in the lack of consistent and standardized field-testing protocols. This report looks at the state of the art of field testing for ADS and identifies areas for improved consistency and standardization. It will define the problem to be addressed by AVs and the challenges associated with the introduction of such vehicles and open-road situations. In particular, the report will look at the…
Annotation ability available
   This content is not included in your SAE MOBILUS subscription, or you are not logged in.

Data Privacy in the Emerging Connected Mobility Services: Architecture, Use Cases, Privacy Risks, and Countermeasures

SAE International Journal of Transportation Cybersecurity and Privacy

Ford Motor Company, USA-Brahim Medjahed, Yu Seung Kim, Pramita Mitra
University of Michigan–Dearborn, USA-Huaxin Li, Di Ma
  • Journal Article
  • 11-02-01-0004
Published 2019-10-14 by SAE International in United States
The rapid development of connected and automated vehicle technologies together with cloud-based mobility services is transforming the transportation industry. As a result, huge amounts of consumer data are being collected and utilized to provide personalized mobility services. Using big data poses serious challenges to data privacy. To that end, the risks of privacy leakage are amplified by data aggregations from multiple sources and exchanging data with third-party service providers, in face of the recent advances in data analytics. This article provides a review of the connected vehicle landscape from case studies, system characteristics, and dataflows. It also identifies potential challenges and countermeasures.
This content contains downloadable datasets
Annotation ability available

Engineered Resilient Systems

  • Magazine Article
  • TBMG-35351
Published 2019-10-01 by Tech Briefs Media Group in United States

Analyzing large data is the process of methodically and systematically making decisions to reduce incomprehensible datasets down to a manageable size that can be viewed and understood easily. These reductions are made by performing data analytics, producing metrics, identifying patterns, and/or producing any other criteria of comparison that can be mathematically modeled.

   This content is not included in your SAE MOBILUS subscription, or you are not logged in.


SAE Truck & Off-Highway Engineering: August 2019

Terry Costlow
  • Magazine Article
  • 19TOFHP08_02
Published 2019-08-01 by SAE International in United States

Data mining helps users and equipment developers use data from on-vehicle sensors to work more efficiently.

The huge volumes of data created by on-vehicle systems are being mined to bring a range of benefits to vehicle operators and fleet managers. Predictive maintenance is becoming more common, while data mining is helping OEM design and manufacturing teams enhance their programs.

Annotation ability available

Overview of the Role of Connected and Autonomous Vehicles in Smart Cities

  • Professional Development
  • C1953
Published 2019-07-15

There is been tremendous progress in the application of technology and artificial intelligence to connected and autonomous vehicles. At the same time, there have been considerable advances in data science and data analysis that allows large data sets to be managed for results. This course introduces big data and analytics, focusing on how these will be applied to data generated by autonomous and connected vehicles. These technologies will be explained within the context of a smart city.