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The development of perception functions for tomorrow’s automated vehicles is driven by enormous amounts of data: often exceeding a gigabyte per second and reaching into the terabytes per hour. Data is typically gathered by a fleet of dozens of mule vehicles which multiply the data generated into the hundreds of petabytes per year. Traditional methods for fueling data-driven development would record every bit of every second of a data logging drive on solid-state drives located on a PC in the vehicle. Recorded data must then be exported from these drives using an upload station which pushes to the data lake after arriving back at the garage. This paper considers different techniques for curating logged data.

Today open source software is widely used in different domains like Desktop systems, Consumer electronics (smart phones, TV, washing machines, camera, printers, smart watches), Automotive, Automation etc. With the increased involvement of the open source software in the different domains including the safety critical ones, there has been a requirement of the well-defined test strategy to test and verify such systems. Currently there are multiple open source tools and frameworks to choose from. The paper describes the various open source test strategies and tools available to qualify such systems, their features, maintenance, community support, advantages and disadvantages. Target audience would be the software engineers, program managers, using an open source stack for the product development.

In the last few years, we have seen a tremendous increase in the rise in product complexity due to advances in technology and aircraft system functionality enhancement. The Model-based Design (MBD) process has helped manage the complexity of these systems while making product development faster by bringing more effective tools and methods to the entire process. Developing software using MBD has required extensive, sophisticated tool-chains that allow for efficient rapid controls prototyping, automatic code generation, and advanced validation and verification techniques using model-in-the-loop (MIL), software-in-the-loop (SIL), and hardware-in-the-loop (HIL) for both component testing and integration testing. However, the MBD process leads to generation of large volumes of data artifacts and work-products throughout the V-Cycle.

It is not news anymore when somebody talks about increasing software content in today's vehicles, transportation systems and machinery. The software content and complexity has grown so tremendously and rapidly that even the most advanced product/software development techniques leave more to desire in view of evolving product life-cycles, feature content and need for development efficiency. Model-Based Design (MBD) techniques and V-Cycle based development processes address the significant need for managing complexity, and to some extent, efficiency in product development. Further efficiency in the development process can be achieved by enabling virtual validation of software components. The virtual validation environment for software not only has the ability to run the software component as a standalone unit for performance validation, but is also extended to the validation of the performance of the entire embedded software of an ECU, multiple ECUs and the entire system.

The Model-Based Development (MBD) process has been the key enabler of technical advancement. MBD helps manage complexity, while making product development faster by bringing clarity and transparency to the entire product development process, specifically software components. Developing software using MBD has required extensive, sophisticated toolchains, like the ones provided by dSPACE, that allow for efficient rapid controls prototyping, automatic code generation, and advanced validation and verification techniques with hardware-in-the-loop (HIL) test systems. MBD is an efficient iterative process that allows engineers to improve quality and deliver on demanding needs of product variants in the current competitive environment. However, the MBD process described commonly using the ‘V-Cycle’ diagram leads to the generation of large volumes of data artifacts and work products. The iterative process, variants and versions of these artifacts lead to even larger amounts of data.

Estimation and prediction of residual life and reliability are serious concerns in life cycle management for aging structures. Laboratory testing replicating fatigue loading for a typical military aircraft wing skin was undertaken. Specimens were tested until their fatigue life expended reached 100% of the component fatigue life. Then, scanning electron microscopy was used to quantify the size and location of fatigue cracks within the high stress regions of simulated fastener holes. Distributions for crack size, nearest neighbor distances, and spatial location were characterized statistically in order to estimate residual life and to provide input for life cycle management. Insights into crack initiation and growth are also provided.

The Controls and Software Engineering Team at BorgWarner Drivetrain Systems has successfully employed model-based software development for the past several years. Their drivetrain system control software, developed using MATLAB/Simulink/Stateflow, and autocoded using TargetLink, is on the road in many passenger vehicle applications. Using these tools, BorgWarner has realized the widely recognized benefits of model-based design; such as increased speed to market, improved quality, and reduced complexity. Validating algorithms early through simulation and rapid prototyping, then translating them to production software through automatic code generation has proven very successful for BorgWarner. When starting with model-based design, the BorgWarner team focused on developing the core application control algorithms in the modeling environment. Lower-level software such as I/O drivers, the task scheduler, and communication logic was still hand-coded.

The enactment of FMVSS 126 requires specific safety performance in vehicles 4,536 Kg (10,000 pounds) or less using an Electronic Stability Control (ESC) system as standard equipment by 2011. Further, in 2012, the regulation requires vehicles that have undergone aftermarket modification to remain in compliance with the performance standard. This paper describes: • a brief overview of the standard and its implications • the collaborative approach used in the first successful approach in meeting that requirement by a lift kit manufacturer o a Hardware In the Loop (HIL) test alternative for establishing a reasonable expectation for a vehicle to demonstrate compliance after modification. • Collaborative challenges overcome: o aftermarket manufacturers seeking information sharing with OEMs and Tier One suppliers: o respecting the intellectual property of OEMs and Tier One suppliers o maintaining the integrity between tool competitors and their customers in cross-collaborative efforts

Model-based software development and automatic production code generation have become increasingly established in recent years. The aerospace industry and other industries, such as automotive, have widely adopted and successfully deployed these methods in many different series production programs worldwide. This brought various benefits, such as a reduction in development times and improved quality due to more precise specifications, and early verification and validation by means of simulation. Model-based development is a general purpose development approach which can be applied to a wide variety of applications. Safety-critical systems, like found in aerospace applications to a large extent, but also found increasingly more often in other industries, like automotive or medical devices, pose special additional requirements to this process. This paper describes how model-based design and automatic production code generation can be applied to the development of safety-critical software.

Over the last few years the introduction of explicit system and software architecture models (e.g. AUTOSAR models) has led to changes in the automotive development process. The ability to simulate these models on a PC will be decisive for the acceptance of such approaches. This would support the early verification of distributed ECU and software systems and could therefore lead to cost savings. This paper describes an implementation of such an approach which fits into current development processes.

This paper gives an overview of a scalable engine management system architecture for motorcycle and other small engine based vehicle applications. The system can accommodate any engine sizes and up to four cylinders. The architecture incorporates advanced functionalities such as oxygen sensing, closed loop fueling, wall-wetting compensation, purge control, start & idle control and deceleration fuel cut-off. Additionally, a number of vehicle-related controls are integrated in the system. Diagnostic and safety related features have also been incorporated with limp-home capability. The software architecture is compatible with different hardware solutions. The system has been implemented in several OEM vehicles around the globe and meets EURO-3 emission requirements.

With increasingly stringent emissions regulations and concurrent requirements for enhanced engine thermal efficiency, a comprehensive characterization of the automotive gasoline fuel spray has become essential. The acquisition of accurate and repeatable spray data is even more critical when a combustion strategy such as gasoline direct injection is to be utilized. Without industry-wide standardization of testing procedures, large variablilities have been experienced in attempts to verify the claimed spray performance values for the Sauter mean diameter, Dv90, tip penetration and cone angle of many types of fuel sprays. A new SAE Recommended Practice document, J2715, has been developed by the SAE Gasoline Fuel Injection Standards Committee (GFISC) and is now available for the measurement and characterization of the fuel sprays from both gasoline direct injection and port fuel injection injectors.

The traditional method of engine knock detection is to compare the knock intensity with a predetermined threshold. The calibration of this threshold is complex and difficult. A statistical knock detection method is proposed in this paper to reduce the effort of calibration. This method dynamically calculates the knock threshold to determine the knock event. Theoretically, this method will not only adapt to different fuels but also cope with engine aging and engine-to-engine variation without re-calibration. This method is demonstrated by modeling and evaluation using real-time engine dynamometer test data.

Virtual design validation of an air induction system (AIS) requires a proper finite element (FE) assembly model for various simulation based design tasks. The effect of the urethane air filter seal within an AIS assembly, however, still poses a technical challenge to the modeling of structural dynamic behaviors of the AIS product. In this paper, a filter seal model and its modeling approach for AIS assemblies are introduced, by utilizing the feature finite elements and empiric test data. A bushing element is used to model the unique nonlinear stiffness and damping properties of the urethane seal, as a function of seal orientation, preloading, temperature and excitation frequency, which are quantified based on the test data and empiric formula. Point mobility is used to character dynamic behaviors of an AIS structure under given loadings, as a transfer function in frequency domain.

A test load specification is required to validate an automotive product to meet the durability and design life requirements. Traditionally in the automotive industry, load specifications for design validation tests are directly given by OEMs, which are generally developed from an envelop of generic customer usage profiles and are, in most cases, over-specified. In recent years, however, there are many occasions that a proposed load specification for a particular product is requested. The particular test load specification for a particular product is generated based on the measured load data at its mounting location on the given type of vehicles, which contains more realistic time domain load levels and associated frequency contents. The measured time domain load is then processed to frequency domain test load data by using the fast Fourier transform and damage equivalent techniques.

In an effort to understand steering systems performance and properties at the microscopic level, we developed Multibody simulations that include multiple three-dimensional gear surfaces that are in a dynamic state of contact and separation. These validated simulations capture the dynamics of high-speed impact of gears traveling small distances of 50 microns in less than 10 milliseconds. We exploited newly developed analytic, numeric, and computer tools to gain insight into steering gear forces, specifically, the mechanism behind the inception of mechanical knock in steering gear. The results provided a three dimensional geometric view of the sequence of events, in terms of gear surfaces in motion, their sudden contact, and subsequent force generation that lead to steering gear mechanical knock. First we briefly present results that show the sequence of events that lead to knock.

Software is today one of the most important components of electronic products. The capture and validation of the requirements makes a difference if the product will fulfill the customer's expectations or generate enormous frustration. The correct implementation of software validation makes the Product Development Organization more mature and reliable. Software validation is an opportunity for the product development team to identify if the requirements and customer expectations were achieved. It is also used to identify the risks and possible improvements to the product. Software testing is one element of a brooder topic that is often referred to as verification and validation (V&V). Verification refers to the set of activities that ensure that software correctly implements a specific function. Validation refers to a different set of activities that ensure that the software that has been built is traceable to customer requirements.

The present work discusses the application of multivariate statistical methods for the analysis of NVH data. Unlike conventional statistical methods which generally consider single-value, or univariate data, multivariate methods enable the user to examine multiple response variables and their interactions simultaneously. This characteristic is particularly useful in the examination of NVH data, where multiple measurements are typically used to assess NVH performance. In this work, Principal Components Analysis (PCA) was used to examine the NVH data from a benchmarking study of hydraulic steering pumps. A total of twelve NVH measurements for each of 99 pump samples were taken. These measurements included steering pump orders and overall levels for vibration and sound pressure level at two microphone locations. Application of the PCA method made it possible to examine the entire set of data at once.

The present work demonstrates the application of Design of Experiments (DOE) statistical methods to the design and the improvement of a hydraulic steering pump noise, vibration, and harshness (NVH) performance in relief. DOE methods were applied to subjective ratings to examine the effect of several different factors, as well as the interactions between these factors on pump relief NVH. Specifically, the DOE was applied to the geometry of the cross ports on a hydraulic relief valve to improve “whistle” noise in the pump. Statistical methods were applied to determine which factors and interactions had a significant effect on pump whistle. These factors were used to produce a more robust cross port configuration reducing whistle noise. Lastly, the final configuration was experimentally verified on the test apparatus and subjectively confirmed in vehicle-level testing.

Determination of the critical speed of a driveshaft is critical for development and validation of its design for use in a vehicle because of its destructive effects. Typical calculations to determine critical speed are either over simplistic and not very accurate or very complicated requiring CAE software and capabilities. An analytical five-section non-prismatic beam model was developed to fill in this gap. The model was developed to compute the critical speed in a worksheet and proven to be as or more accurate as utilizing FEA methods. The model worksheet calculates the critical speed for one-piece conventional driveshafts and adapted for Visteon's Slip-In-Tube (SIT) driveshafts.