One of the benefits of VeSyMA, and simulation in general, is the ability to answer “what if” questions using predictive models in experiments such as drive cycles. Sensitivity testing is a common and effective method of study. One parameter of a model is varied, with all others kept static, to determine which parameter the overall performance is most sensitive to.
When looking to improve a design, it must be known first where the design needs to be improved. Therefore, sensitivity testing is useful, enabling precise effects of various parameters to be understood. Developing electric vehicles is no different, with a plethora of environments to be deployed in; road with gradients, driving in crosswinds and adding a roof storage box.
The VeSyMA library itself, which the wider VeSyMA suite is built upon, is able to undertake straight-line drive cycle simulation. For this blog post, a VeSyMA library experiment will be used to explore the effect on battery state of charge (SOC) of various common scenarios encountered by an EV.
Drive-cycle experiment
Specifically designed to be easy to use for investigative studies, VeSyMA drive cycle experiments feature vehicles limited to longitudinal studies. This way, accurate and measurable drive cycle analysis can be performed.
From the VeSyMA library, the example DriveCycleElectric experiment was used – VeSyMA.Experiments.Examples.DriveCycleElectric. This features a RWD Executive class vehicle, equipped with a single 350Nm electric motor.

Figure 1: Drive cycle experiments comprise of a vehicle, with a closed loop driver model to drive the vehicle in accordance with the drive cycle target.
The closed loop driver model was not changed in between tests. A NEDC (New European Drive Cycle) target was used for the driver model to achieve using the EV. By default, the example test featured no road gradient (completely flat) and no wind. Total drive cycle length was 123.706km.

Figure 2: The NEDC was used for this study.
Drive cycle scenarios
In addtion to the basic stock EV drive cycle, 3 scenarios were investigated:
- 2% road gradient: A 2% road gradient was applied along the 123km drive cycle. This meant a total climb of 2.47km during the cycle
- 25mph crosswind: A crosswind at 30 degrees to vehicle centerline was applied against the front of the vehicle, of 25mph or 11.176ms-1 .
- 50kg roof box: An additional storage box of 50kg mass was affixed to the vehicle. The extra 0.437m2 of frontal area was estimated and added to the vehicle body drag calculation. Note: without data regarding the drag coefficient of the roof box, the vehicle Cd was not changed. If data were available for this, then it would be simple to include this effect in the study.
Drive cycle results
All 3 scenarios saw an increase in the consumption of the battery versus the stock drive cycle. Of all the scenarios, the additional road gradient impacted the battery the most.

Table: Tabular results for the drive cycle scenarios
Reviewing the graphical results, we see that the biggest differences correlate with the latter part of the test. This is predicable, as the last portion of the drive cycle has the highest velocity to reach and hold.

Figure 3: Graphical results of the drive cycle testing.
Closing remarks
Whilst this study was a rudimentary demonstration of what could be done with the VeSyMA library, it provides some interesting results and talking points. It’s clear to see that the road gradient has the biggest effect in our study, and the climb across the drive cycle was not what would be considered excessive, or mountainous. From a study like this, one could deduce that considering the geography of the terrain the vehicle is going to be used on to be of prime importance when designing the vehicle.
Such a study could be taken much further. Is the vehicle undertaking such a climb because the occupants are on a holiday to the mountains? Will they have a larger luggage load because of this? Is it likely to be windy? Could they have significant extra aero drag items attached externally on the car? With VeSyMA, all of this and more can be explored, using the VeSyMA library itself.
Written by: Theodor Ensbury – Project Engineer
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