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Systems engineering is not a new discipline for todays automotive OEMs and suppliers. So, why is it that many feel the discipline is under-utilized or not utilized at all in main-stream product development? For those that do believe systems engineering is a key activity in the development cycle, why is it common to disagree on a definition of what it is or how it manifests itself in the development cycle? If we examine the development activity of leading OEM's and suppliers in any industry, there can be no doubt that product development is a complex and intensive activity. Many disciplines are utilized with many specialized skills deployed throughout the lifecycle of the typical product, and even more so in the automotive industry. One can point to several processes that seem to indicate the presence of systems engineering, yet the ability to clearly define whether or not - and to what degree - we leverage systems engineering is still difficult.

Driven by the desire to implement low-cost, high-efficiency NOx aftertreatment systems, such as Three Way Catalysts (TWC) or Lean NOx Traps (LNT), a novel 6-Stroke engine cycle was explored to determine the feasibility of implementing such a cycle on a compression ignition engine while continuing to deliver fuel efficiency. Fundamental questions regarding the abilities and trade-offs of a 6-stroke engine cycle were investigated for near-stoichiometric and lean operation. Experiments were performed on a single-cylinder 15-liter (equivalent) research engine equipped with flexible valvetrain and fuel injection systems to allow direct comparison between 4-stroke and 6-stroke performance across multiple hardware configurations. 1-D engine simulations with predictive combustion models were used to support, iterate on, and explore the 6-stroke operation in conjunction with the experiments.

Designing a lightweight and durable engine is universally important from the standpoints of fuel economy, vehicle dynamics and cost. However, it is challenging to theoretically find an optimal solution which meets both requirements in products such as the cylinder head, to which various thermal loads and mechanical loads are simultaneously applied. In our research, we focused on “non-parametric optimization” and attempted to establish a new design approach derived from the weight reduction of a cylinder head. Our optimization process consists of topology optimization and shape optimization. In the topology optimization process, we explored an optimal structure with the theoretically-highest stiffness in the given design space. This is to provide an efficient structure for pursuing both lightweight and durable characteristics in the subsequent shape optimization process.

Sensor selection for the control of modern powertrains is a recognised technical challenge. The key question is which set of sensors is best suited for an effective control strategy? This paper addresses the question through probabilistic modelling and Bayesian analysis. By quantifying uncertainties in the model, the propagation of sensor information throughout the model can be observed. The specific example is an abstract model of the slip behaviour of Selective Catalytic Reduction (SCR) DeNOx aftertreatment systems. Due to the ambiguity of the sensor reading, linearization-based approaches including the Extended Kalman Filter, or the Unscented Kalman Filter are not successful in resolving this problem. The stochastic literature suggests approximating these nonlinear distributions using methods such as Markov Chain Monte Carlo (MCMC), which is able in principle to resolve bimodal or multimodal results.

Acoustic comfort of automotive cabins has progressively become one of the key attributes of passenger comfort within vehicle design. Wind noise and the heating, ventilation, and air conditioning (HVAC) system noise are two of the key contributors to noise levels heard inside the car. The increasing prevalence of hybrid technologies and electrification has an associated reduction in powertrain noise levels. As such, the industry has seen an increasing focus on understanding and minimizing HVAC noise, as it is a main source of noise in the cabin particularly when the vehicle is stationary. The complex turbulent flow path through the ducts, combined with acoustic resonances can potentially lead to significant noise generation, both broadband and tonal.

In use cars often drive through the wakes of other vehicles. It has long been appreciated that this imposes a fluctuating onset flow which can excite a structural response in vehicle panels, particularly the bonnet. This structure must be designed to be robust to such excitation to guarantee structural integrity and maintain customer expectations of quality. As we move towards autonomous vehicles and exploit platoons for drag reduction, this onset flow condition merits further attention. The work reported here comprises both measurements and simulation capturing the unsteady pressure distribution over the bonnet of an SUV following a similar vehicle at high speed and in relatively close proximity. Measurements were taken during track testing and include 48 static measurement locations distributed over the bonnet where the unsteady static pressures were recorded.

Never in the history of the automotive industry has it been more critical for automakers to prove that they are capable of producing vehicles efficiently and cost-effectively. In the coming months and years there will be a growing requirement for lean product design and manufacturing strategies that will re-shape the way the automotive suppliers and OEMs conduct business. Computer-aided-design and manufacturing have become commonplace in automotive product design and manufacturing processes. These technologies enable efficiencies and quality improvements through virtual simulation and testing of kinematic designs. However, to date, there has been no ability to incorporate the process controls into these simulations. Vehicle introductions require new manufacturing processes and equipment which is typically outsourced by the OEMs to a supplier.

The swivel-type hinge mount specified in SAE J180 has been the standard alternator mounting for many years. However, in the mid-1990's on-highway applications began to experience vibration related failures due to casting excitation. This led to the eventual development of a stationary “pad mount” system in combination with an automatic belt tensioner. This paper will review the system component life and benefits of pad mount, and proposes an industry mounting standard for further application usage.

The use of a partial flow sampling system (PFSS) to measure nonroad steady-state diesel engine particulate matter (PM) emissions is a technique for certification approved by a number of regulatory agencies around the world including the US EPA. Recently, there have been proposals to change future nonroad tests to include testing over a nonroad transient cycle. PFSS units that can quantify PM over the transient cycle have also been discussed. The full flow constant volume sampling (CVS) technique has been the standard method for collecting PM under transient engine operation. It is expensive and requires large facilities as compared to a typical PFSS. Despite the need for a cheaper alternative to the CVS, there has been a concern regarding how well the PM measured using a PFSS compared to that measured by the CVS. In this study, three PFSS units, including AVL SPC, Horiba MDLT, and Sierra BG-2 were investigated in parallel with a full flow CVS.

Thermal management on aircraft has been an important discipline for several decades. However, with the recent generations of high performance aircraft, thermal management has evolved more and more into a critical performance and capability constraint on the whole aircraft level. Fuel continues to be the most important heat sink on high performance aircraft, and consequently the requirements on thermal models of fuel systems are expanding. As the scope of modeling and simulation is widened in general, it is not meaningful to introduce a new isolated modeling and simulation capability. Instead, thermal models must be derived from existing model assets and eventually enable integration across several physical domains. This paper describes such an integrated approach based on the Modelica Fuel System Library and the 3DExperience Platform.

Internal combustion (IC) engines that meet Tier 4 Final emissions standards comprise of multiple engine operation and control parameters that are essential to achieve the low levels of NOx and soot emissions. Given the numerous degrees of freedom and the tight cost/time constraints related to the test bench, application of virtual engineering to IC engine development and emissions reduction programmes is increasingly gaining interest. In particular, system level simulations that account for multiple cycle simulations, incylinder turbulence, and chemical kinetics enable the analysis of combustion characteristics and emissions, i.e. beyond the conventional scope of focusing on engine performance only. Such a physico-chemical model can then be used to develop Electronic Control Unit in order to optimise the powertrain control strategy and/or the engine design parameters.

Today's engineers must meet program management demands within the context of the challenges facing the industry as a whole. Resource scarcity, both people and capital, is forcing the automotive industry to optimize the deployment and consumption of enterprise resources. As globally dispersed project teams become more commonplace, efficient and effective communication across geographies is critical. Market segmentation and technology are influencing how well manufacturers deliver products within performance and timing guidelines. Future success means providing global engineering teams with state- of- the- art tools and processes to unify disparate business groups in a virtual workspace -24/7. The solution to this is Product Lifecycle Management (PLM), a strategic business approach that supports collaborative creation across the enterprise and all stakeholders. PLM solutions link information from different authoring tools and others systems to the developing product configuration.

Mechatronics development continues to be a challenge for automotive OEM's and suppliers. Multi-disciplinary collaboration and development is critical, especially as architectures and solutions evolve in the automotive industry to satisfy changing needs of the customer and environment. New approaches to mobility, sustainment, and infotainment create the need for new combinations of electrical, software, mechanical, and chemical know-how. Whereas most frameworks for requirements-driven model-based design support a single discipline, what is really needed is a framework for requirements-driven model- based design that can capture the multi-disciplinary architecture of the vehicle or system. This would and allow development organizations to then further decompose the objects in support of further refinement and validation.

The Aerospace and Automotive industries face increasing product complexity and shortening of product development cycles. One critical means companies in these industries strive to directly overcome these challenges is through modeling and simulation. Beginning at the earliest phases in the new product development process, companies derive additional value through increased deployment of simulation across the entire product life-cycle. This paper discusses three areas: 1) the business case for change; 2) technology enablement of the various types of model-based simulators; 3) institutional mobilization to move to a new enterprise state that embraces new ways of working and engaging with existing and prospective customers. The business case for change focuses on two main points in acquisition: developing a detailed understanding of the system needs and systematically working through the techno-economic estimation challenges.

To increase sales and market position, automotive OEMs must have comprehensive strategies for developing innovative products while continuing to reduce costs, increase quality and accelerate time to market. One of the strategies that can help them to achieve these objectives is strategic modularity. A modularization strategy can help automakers reduce cost and time to market, as well as improve quality and launch readiness. While a significant number of OEMs are adopting modularity strategies, the realization of benefits has been, for many OEMs, limited in scope and scale. These limitations are due to: Process issues in managing dependencies across multiple programs and platforms; Measurements which discourage modularity adoption, together with an inability to measure enterprise costs; Organizational issues associated with siloed structures, a lack of clear roles and responsibilities, and the management of disparate groups across the extended enterprise.

The development of new vehicle is becoming increasingly complex: proliferation of on-board electronics, development of hybrid advanced powertrain technologies, globalization of design and production, to name a few. At the same time, companies are straining constantly to better meet consumer desires while reducing time to market and production costs. Definitely a tough challenge! The ever growing amount of data (both in variety and in number of sources) that the enterprise generates is central to this situation. Compiling and processing this data efficiently is easier said than done. And failure to do so can lead to critical business opportunities being lost! A solution exists. It comes from the web where an innovative approach was indeed mandatory to cope with the billions of documents to search. It is called “search technology” and is engrained in the DNA of EXALEAD.

Government regulations and consumer needs are driving automotive manufacturers to reduce vehicle energy consumption. However, this forms part of a complex landscape of regulation and customer needs. For instance, when reducing aerodynamic drag or vehicle weight for efficiency other important factors must be taken into account. This is seen in vehicle bonnet design. The bonnet is a large unsupported structure that is exposed to very high and often fluctuating aerodynamic loads, due to travelling in the wake of other vehicles. When travelling at high speed and in close proximity to other vehicles this unsteady aerodynamic loading can force the bonnet structure to vibrate, so-called “bonnet flutter”. A bonnet which is stiff enough to not flutter may be either too heavy for efficiency or insufficiently compliant to meet pedestrian safety requirements. On the other hand, a bonnet which flutters may be structurally compromised or undermine customer perceptions of vehicle quality.

Design of HVAC system plays an important role in acoustic comfort for passengers. With automotive world moving towards electrical vehicles where powertrain noise is low, designing low noise HVAC system is becoming more important. For an automobile manufacturer, ability to predict the production vehicle cabin noise at the early design stage is important as it allows more freedom for design changes, which can be incorporated in the vehicle at lower cost. Although HVAC prototype and system level testing at early design stage is possible for noise estimation but flow field is not visible in test that makes difficult to improve design. CFD simulation can provide detailed information on flow field, noise source strength and location. But in such a simulation, accurate prediction has been a challenge due to the inability of CFD tools to model acoustic absorptive characteristics of interior walls of cabin.

It is particularly easy to get tunnel vision as a domain expert, and focus only on the improvements one could provide in their area of expertise. To make matters worse, many Original Equipment Manufacturers (OEMs) are silo-ed by domain of expertise, unconsciously promoting this single mindedness in design. Unfortunately, the successful and profitable development of a vehicle is dependent on the delicate balance of performance across many domains, involving multiple physics and departments. Taking for instance the design of a Heating, Ventilation & Air Conditioning (HVAC) system, the device’s primary function is to control the climate system in vehicle cabins, and more importantly to make sure that critical areas on the windshield can be defrosted in cold weather conditions within regulation time. With the advent of electric and autonomous vehicles, further importance is now also placed on the energy efficiency of the HVAC, and its noise.

It is a time and cost consuming way to physically develop Hybrid Electric Vehicle (HEV) supervisor controller due to the increasing complexity of powertrain system. This study aims to investigate the HEV supervisor controller development process using dSPACE midsize Hardware in the Loop simulation system (HIL) for HEV powertrain control. The prototyping controller was developed on basis of MircoAutoBox II, and an HIL test bench was built on midsize HIL machine for the purpose of verification. The feasibility and capability of HIL were attested by the prototyping control strategy and fault modes simulation. The proposed approach was demonstrated its effectiveness and applicability to HEV supervisor controller development.