Vehicles are getting ever more complex, with subsystems becoming increasingly interdependent and the system dynamics wider than ever before. Modern vehicles now interact with their surroundings, reacting and responding to changes in the immediate environment. This is particularly true in autonomous vehicles. Consideration of the higher-level system effects on subsystem behaviour and vice-versa is now of paramount importance, including environmental interactions with the vehicle.
Systems engineering tools are required to be capable of considering the vehicle not only in a holistic total system manner, but also as a function of the environment.
Systems engineering consultancy Claytex is expert in the application of Dymola, the Dassault Systèmes simulation tool, for automotive and motorsport. The Warwickshire-based company offers customers a comprehensive suite of solutions that enable the modelling, simulation, and testing of a vehicle in virtual environments.
Last year Claytex completed the development of a suite of libraries for Modelica (the acausal, object orientated modelling language behind Dymola). The ‘Vehicle Systems Modelling and Analysis’ libraries or VeSyMA, launched in May 2017, provide models for the simulation of conventional, hybrid and electric vehicles, as well as motorsport applications. VeSyMA offers a set of vehicle templates with the flexibility to reconfigure subsystems and architectures to address any vehicle architecture concept. VeSyMA is intended to help designers and engineers combine different aspects – propulsion systems, powertrain, suspensions and so forth – of a vehicle architecture.
“Players in the autonomous vehicles sector need to take the significance of vehicle physics seriously when deploying simulation tools. It is necessary to have a correct physics model inside these simulators in the longer term. This is because engineers need to reliably predict how an autonomous vehicle will respond in relation to internal and external situations and how to manage the vehicle’s response,” says Claytex managing director Mike Dempsey.
Another challenge is to build a deeper understanding of how real-world factors are likely to impact the performance of sensors when deployed in autonomous vehicles. “For example, how to account for different weather conditions. With a lidar sensor, as soon as the humidity increases, the distance it can see starts to drop off. When it rains, increased ‘scatter’ means that the performance of the sensor drops off. We need to be able to look at how we characterise the sensor behaviour and build such contingencies into the model”, adds Dempsey.
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