Studying Vehicle Behavior in Real Driving Scenarios with GT-RealDrive
The continual tightening of vehicle emission standards has led to decreases in pollution associated with vehicles but not to the levels that the standards target. Research into why has highlighted a disconnect between the emissions emitted by vehicles during real-world driving versus under laboratory conditions. This disconnect is mostly caused by the fact that laboratory drive cycles don’t properly represent the range and variety of conditions that occur in real driving scenarios (ex. cold ambient temperatures, driver behavior, road grade).
As a result, many regulatory bodies around the world have started to adopt regulations that attempt to establish vehicle emission standards that apply to real-world driving. Such standards, commonly referred to as Real Driving Emissions (RDE), usually mean that the vehicle is driven on public roads while recording emissions rather than doing so in a controlled laboratory setting. This is also occasionally called off-cycle driving, as the vehicles are not being driven using standard regulatory cycles such as the WLTC, FTP-75 or JC08.
This presents a large challenge to the automotive industry which needs to ensure that vehicles are compliant with emission regulations under real driving conditions that vary greatly and are only defined as a set of boundary conditions. Testing can be conducted to try and ensure compliance, but it is both costly and can only be carried out once a prototype vehicle is built. Relying on testing alone is a huge risk. If a vehicle is discovered to be non-compliant late in the development process, it will likely result in delays and it will be extremely costly to re-design the powertrain and aftertreatment system.
To help engineers mitigate the risk that a vehicle won’t meet the applicable real driving emission standards, we developed simulation solutions such as vRDE. The latest development is GT-RealDrive, a route generation tool that helps engineers study how vehicle and system models perform under real-driving scenarios.
GT-RealDrive models real-world driving by creating off-cycles routes based on user defined start and end addresses. The cycles take into account traffic conditions, elevation, and traffic signals, effectively generating a cycle representative of real-world driving. Since GT-RealDrive is self-contained within GT-SUITE, the drive cycles created can be directly used in any GT-SUITE vehicle model to simulate off-cycle driving in the same manner as the standard regulatory cycles.
Let us now explore an example of how easily engineers can use GT-RealDrive to generate real-world routes to aid in their vehicle development process.
In this example, a user is tasked with comparing the estimated real-world and on-cycle fuel economy of a new passenger car under development by their company. Since this is relatively early in the development stage of the car, no hardware is available yet. However, the current design is known and was previously modeled in GT-SUITE. Thus, the user has a full vehicle model to generate an estimated on-cycle fuel economy number.
To accomplish this task, the user decides to generate numerous off-cycle routes, simulate the vehicle driving the routes, record the resulting fuel economy, and average the results.
The user starts by generating a route for the daily commute of someone living in Downtown Chicago who works in the suburbs. This route is created by accessing the GT-RealDrive tool directly within GT-SUITE and inputting the start and end locations. These locations can be entered as an address or as the name of a place (for example, The United Center). The tool includes suggestions/autocomplete as one typically experiences when using an online map. Several route options can then be specified (ex. Avoid Toll Roads) in addition to adding a Via-Point if desired.
For our example, this fictional commute is from the Gamma office in Westmont, IL to the Aqua Condo Building in Chicago, IL. The image below illustrates both the autocomplete and name to address conversion feature included in GT-RealDrive.
Once the data is input and the desired options are selected, the “Plan Route” button is pushed. This is when the behind the scenes magic occurs; the route is created based on the directions between the start and end locations and current traffic conditions, which are supplied by a service called Mapbox. The route is plotted on the map and the resulting data is populated in the table.
This data represents the route and includes a list of coordinates, target vehicle speeds, traffic congestion and speed limits. Users can also choose to include other important factors such as elevation data and traffic signals in this output data. By outputting the data into this editable table, users are able to modify the route to their liking and make minor changes such as adding or removing Traffic Signals, setting unique Stop Duration times at specific intersections or modifying the Vehicle Target Speed.
This route is now available to be used in GT-SUITE to test how the vehicle model will perform on the route. All that the user has to do is open the full vehicle model and swap out the regulatory cycle with the off-cycle route.
In this scenario, the engineer would continue to generate a wide variety of additional routes to simulate in the vehicle model, then record the fuel economy and compile the results. Once a sufficient number of routes have been tested, the user has the data needed for an accurate comparison of the real-world and on-cycle fuel economy of the vehicle in development.
The application of such real-world driving cycles extends far beyond just simulating light and heavy-duty vehicle emissions for regulatory compliance purposes (i.e. RDE, In-Service Conformity, and Heavy-Duty In-Use Testing). It can also be used to investigate topics such as real-world EV range & energy management, effects of driver behavior, thermal management, component mechanical durability loading conditions, and control strategies/algorithms; the only limit is your imagination.
One key use is to study the ageing of batteries in EVs when they are driven with real-world drive cycles. A DOE could be created to investigate the effect of driver behavior, ambient conditions and traffic to better understand the variation that these factors have on EV range. This could then be taken a step further to investigate range prediction given some, or even all, of the above factors.
GT-RealDrive presents an integrated solution to discover how vehicle models will perform on real-world routes. There is no need to collect and process expensive GPS driving data or to format data for importing into GT-SUITE. With GT-RealDrive and an internet connection, users generate real-world routes to aid in their vehicle development from RDE compliance tests to EV range prediction and beyond.
If you are interested in trying out GT-RealDrive or would like more details please reach out and contact us.
Written By: Phil Mireault