MODELLING AND SIMULATION The Need for Speed SIMULATION AND
MODELLING INCREASINGLY EXPEDITE WIDESPREAD CHANGE ACROSS THE AUTOMOTIVE INDUSTRY, WRITES GEMMA CHURCH
The automotive sector is undergoing a period of rapid and disruptive transformation from
both a business and technical standpoint. The industry is increasingly using simulation and modelling to help both experienced OEMs and new players get their latest products to market as quickly as possible. Alan Prior, senior director of technical sales, EuroNorth at Dassault Systèmes, said: ‘The last three to four years have brought more change than the last three decades. The key challenge is that all parties need to be able to work faster – and this is the challenge simulation and modelling can address for the automotive industry.’
This intrinsic need to work faster comes about as a result of a range of interlinking factors in the automotive sector. ‘There are three major and current trends pushing change: the emergence of new players in the business; new technologies such as electrification and automation; and the shift to a systems-based approach,’ Prior explained. MDGo is one such startup in the
automotive space. The company has designed a system that automatically alerts first responders and hospitals when there’s an incident on the road and provides them with information based on measurements taken from the vehicle’s sensors during a collision. Research shows that up to 44 per cent of people who died in car crashes could have been saved if first responders and hospitals had real-time, detailed information about the victim’s injuries. Eli Zerah, co-founder and VP of R&D at
MDGo, explained: ‘Our algorithm requires a massive amount of diverse data in order
26 Scientific Computing World June/July 2019 Simulation results from Altair Hyperworks @scwmagazine |
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to learn how to predict the forces applied to passengers, given the vehicle sensor measurements. Unfortunately, most crash tests are limited to a few specific scenarios dictated by regulation. Relying on these, solely, results in small amounts of data, with very limited scenarios lacking the representation of a lot of real-life cases.’ The company used Altair Radioss
to conduct its crash simulations. By combining these results with actual sensor data from car accidents, the system could predict potential occupant injuries. Zerah explained: ‘Simulation and modelling gave us the much-needed flexibility to gain results of any real-life scenario we like. We were able to grow from five specific [crash] scenarios to dozens of different cases differing in angle, barrier type, velocity, and so on. It also gave us the opportunity to increase the total amount of cases that we use for our algorithm training. ‘Simulations are a key enabler of our R&D process, therefore, we plan to continue using this tool in order to diversify our data in all verticals, scenarios, vehicle models and human models,’ he added.
This highlights another important
application for simulation and modelling in the changing automotive industry. Namely, that any new technology entering the market requires thorough testing to ensure it meets the industry’s strict safety standards. But new ways of working need to be developed, because of the new
technologies entering the market. Gilles Gallée, business development director for autonomous driving at ANSYS, explained: ‘Autonomous vehicle and embedded software safety will make the expenditure for validation increase by a factor of 106 to 107. Because traditional statistical validation is not suitable anymore, autonomous systems require completely new release strategies. ‘New strategies include using simulation
to achieve the complete digital safety of the car [and] driving millions of miles virtually, in order to produce 99 per cent of the validation through simulation, while completing the remaining testing with physical on-road driving,’ he added. ANSYS is focused on five ‘major disruptions’ in the automotive industry, according to Gallée, each of which brings further challenges to the sector. These include autonomy (where development and testing require more than eight billion miles of road tests, equivalent to 1,000+ years of drive time); electrification (where battery costs must be reduced three- fold); safety (where new qualifications require ten times the validation effort); additive manufacturing (for a vast range of new topologies); and smart connectivity (where vehicles now rely on millions of lines of code), Gallée explained. Altair is also working ‘aggressively’
in three main areas, according to Uwe Schramm, CTO of HyperWorks core development at the company. These areas include the simulation and modelling of lightweight designs, the e-powertrain (found in electric vehicles to replace
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