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Accelerating product development cycles and incentives to reduce costs in product development are strong motivators to move to virtual development and validation processes. Challenges to moving to a virtual paradigm include a wealth of historical data and context for hardware tests, uncertainty over dependencies, and a lack of a clear path of transition to virtual methods. In this paper we will discuss approaches to understanding the value created by hardware tests and aligning that value to virtual processes. We will also discuss the need for a virtual context to be added to SAE J1739 [1] (DFMEA detection criteria), and how to create paths to maximize the value of virtual assessments. Finally, we will also discuss the cultural and organizational changes required to support.

As passenger vehicle design evolves and accelerates, the use of multi-body dynamics solvers has proven to be invaluable in the engineering workflow. MBD solvers allow engineers to build virtual vehicle models that can accurately simulate vehicle responses and calculate internal forces, which previously could only be assessed using physical prototype builds with hundreds of measurement transducers. Evaluation and selection of solvers within an engineering environment is inherently a multi-dimensional activity that can include ease of use, retention of previously developed expertise, accuracy, speed, and integration with existing analysis processes. We discuss here some of the challenges present in developing capability and accumulating data to support each of these criteria. Developing a pilot model that is capable of being applied to a comprehensive set of use cases, and then verifying those use cases, required significant project management activity.

Exterior component integration presents competing performance challenges for balanced exterior styling, safety, ‘structural feel’ [1] and durability. Industry standard practices utilize noise and vibration mode maps and source-path-receiver [2] considerations for component mode frequency placement. This modal frequency placement has an influence on ‘structural feel’ and durability performance. Challenges have increased with additional styling content, geometric overhang from attachment points, component size and mass, and sensor modules. Base excitation at component attachment interfaces are increase due to relative positioning of the suspension and propulsion vehicle source inputs. These components might include headlamps, side mirrors, end gates, bumpers and fascia assemblies. Here, we establish basic expectations for the behavior of these systems, and ultimately consolidate existing rationales that are applied to these systems.

The automotive industry is under great pressure to reduce vehicle mass for both cost and fuel economy gains. A significant contributor to body and suspension structure mass is peak vertical loads, primarily entering the body structure through the jounce bumper to body interface. This paper focuses on the successful development of “Loads Management Striker Caps” for the 2013 Cadillac ATS front and rear suspension. Component design and development of the striker caps was executed using explicit finite element analysis tools. Multi-body dynamics vehicle models were used to set component requirements and confirm striker cap performance for the vehicle during peak vertical events. The “Loads Management Striker Caps” ultimately reduced peak strut/shock tower loads by 40% in the front suspension and 25% in the rear suspension. This resulted in significant body and chassis mass savings, contributing to the Cadillac ATS's class leading curb weight.

Global programs are placing demands on vehicle platforms to achieve structural durability robustness across a broader spectrum of vehicle configurations and use conditions. This robustness is optimally achieved by (a) localizing energy absorption to lower cost components, and (b) narrowing the spread in loads generated during durability events, which in turn minimizes the cost and mass impact to the vehicle platform. A generalized philosophy for conducting load optimization and for improving energy management for various types of events is presented here. Various techniques that have been employed at GM are explained by way of illustration.

Jounce bumpers are the primary component by which vertical wheel travel is limited in our suspensions. Typically, the jounce bumper is composed of closed or open cell urethane material, which has relatively low stiffness at initial compression with highly progressive stiffness at full compression. Due to this highly progressive stiffness at high load, peak loads are extremely sensitive to changes in input energy (affected by road surface, tire size, tire pressure, etc.) A “Dual Rate Jounce Bumper” concept is described that reduces this sensitivity. Additionally, various mechanizations of the concept are described as well as the specific program benefits, where applicable.

Measured vehicle loads have traditionally been used as the basis for development of component, subsystem and vehicle level durability tests. The use of measured loads posed challenges due to the availability of representative hardware, scheduling, and other factors. In addition, stress was placed on existing procedures and methods by aggressive product development timing, variety in tuning and equipment packages, and higher levels of design optimization. To meet these challenges, General Motors developed new processes and technical competencies which enabled the direct substitution of analytically synthesized loads for measured data. This process of Virtual Road Load Data Acquisition (vRLDA) enabled (a) conformance to shortened product development cycles, (b) greater consistency between design targets and validation requirements, and (c) more comprehensive data.

Measured vehicle loads, taken during durability events, are commonly used to drive in-lab vehicle subsystem validation testing. The use of measured loads can be problematic due to (a) off-nominal characteristics of the test vehicle, (b) post-test changes to vehicle tuning - bushings, springs, and shocks for example, (c) scheduling, timing and weather requirements, (d) modification of vehicle characteristics by the inclusion of transducers and (e) the cost of executing tests. A general process for supplementing and rationalizing measured vehicle data through the use of correlated multi-body dynamic simulations is presented. Difficulties in modeling tires and other components, as well as difficulties in model correlation for abusive load events are also discussed.