Simulation Techniques that Accelerated the Development of the Lightyear One

Together with Ansys, a developer of simulation software, we are creating a series of content about the technologies that make sustainable transportation possible. Read the foundation article of the series here.

Lightyear is developing long-range solar electric vehicles, based on the holistic design philosophy that clean mobility is for everyone. In this article, we’ll explore how simulation technologies enabled the design of their flagship vehicle, Lightyear One. 

How Simulation Was Used to Develop Lightyear One

Lightyear is a lean start-up, which means the engineering team needs to use every resource as efficiently as possible. An iterative, simulation-heavy approach to design is essential to the success of the business. To design Lightyear One as fast, effective, and efficient as possible, simulation techniques were employed across departments. 

Solar Panel Development

Before discussing the techniques used to optimize the solar panels of Lightyear One, it’s worth revisiting why very few other automotive companies have attempted the solution. The practical limitations of solar energy are apparent:

• Ideal harvesting times are around noon only;

• Cloudy and rainy climates limit the ability to charge with solar alone;

• Even large, efficient panels are slow to charge compared to what a customer could use for fuel (plugging into an electrical outlet or even fueling up with petrol).

Lightyear knows that, although not the fastest method of charging, solar is one of the cleanest sources of energy and can be integrated to boost the vehicle’s efficiency. Charging infrastructure to support electric cars also adds a step on the path to clean mobility. Thus, Lightyear simply develops solar cars to harvest the energy from its source: the sun. For customers that drive infrequently or have a very short commute (<30 km/day), it means they could use only the sun to keep their EV charged, making it inexpensive and green. On top of that, the slower charge provided by solar is also better for the overall life of the battery, further improving potential maintenance costs. 

The constraint of the use of solar panels in automotive design is the structural requirements for any large body panels. In the event of a crash, the solar panels would need to perform as well as a typical steel, aluminum, or glass roof structure, in order to protect the occupants. To mitigate the effect of shadows and other mismatches between solar irradiance and curvature, the panels were divided into small groups (or layers) electrically.

Structural simulations were then conducted on the layered design, to ensure the panels could withstand both normal wear and tear (through fatigue testing) and maximum loading conditions (which allowed for shape and material optimization). In addition, crash test simulations were also completed on an FEA model of the chassis, including the solar panels. While certification of a new vehicle requires a physical crash test, the simulations expedite the design to a place where fewer mule cars need to be built, and the design solution is much closer to the final iteration. 

Aerodynamic Efficiency Achieved through CFD Simulation

The engineering team’s mandate was to make the most of the energy obtained from the sun. The 12 km range for one hour of sunshine needed to be put to the best use possible, so aerodynamicists were tasked with minimizing drag. Their efforts were impressive, with an overall CD of less than 0.20. The sub-0.20 metric is significant, seeing how Tesla previously flaunted its 0.208 CD for the new Model S as the most aerodynamic production car on the planet. 

Similar to the structural simulations for the solar panels, computational fluid dynamics (CFD) software is used throughout aerodynamic design and testing. Wind tunnel tests are expensive and require a scale or full-size model/mule car to be built, which is often less efficient than using the CAD model already in existence for simulation. 

CFD Engineers clean up the CAD model so that surfaces are watertight and are named/subdivided in such a way that their mesh will be generated as intended. They can use a variety of flow simulation techniques as well. Often, steady-state full-vehicle aerodynamic simulations using a Reynolds-Averaged Navier-Stokes (RANS) approach will often be done first. Then, by comparing design iterations, the delta in overall forces (drag and lift), as well as balance (percentage lift on the front axle) can be quickly determined. This is how the overall shape of the design can be selected, as well as optimize smaller components (mirrors, spoilers, air dams, etc.). In addition, engineers can finalize the vehicle’s surfaces using CFD, such as the front fascia, rear deck, and even the underfloor, which can generate significant drag. 

Lightyear One is unique in its profile, the fastback shape (sometimes referred to as a longtail design) isn’t a typical (or popular) choice among traditional automakers. The aerodynamicists at Lightyear explain that, while they do have to make compromises with the designers for the look and styling of the car, they are given the overall power to determine the overall form, as long as it minimizes drag, and, therefore, increases efficiency. By maintaining the curvature of the roofline all the way to the tail, form drag (or pressure drag) is minimized. 

Similarly, the wheel covers featured on Lightyear One’s rear wheels are rare in contemporary car design, as designers love to showcase beautiful rims. But the drag generated by a rotating rim and tire can be significantly reduced by diverting the freestream air from entering the wheel well, using air dams or deflectors, such as wheel covers. 

Transient simulation techniques using an unsteady RANS model, large eddy simulation (LED), or detached eddy simulation (DES) and wind tunnel testing are used sparingly to get more accurate results. To determine the reported <0.20 drag coefficient, a wind tunnel test was conducted. For Lightyear, wind tunnel testing was reserved for correlation (to simulation results) and for reporting these final, overall published metrics. In the spirit of the company’s mission, simulation also cuts down on the energy consumed when building models, running a wind tunnel and transporting experts to the test. While running the computations in the cloud is not free from energy usage, it’s significantly less than physical testing. 

Electromagnetic and Thermal Simulations

In addition to the more obvious simulation methods, Lightyear (and other EV firms) make use of electromagnetic and thermal simulations. While testing plays a role, it’s difficult to visualize or monitor all aspects of a test. Simulation provides invaluable post-processed visualizations and data, which help engineers understand the system and where to make improvements. 

The in-wheel motors that Lightyear specifically designed provide power-on-demand and independence. Not only does this allow for torque vectoring and optimized traction, it also eliminates many large components. Traditional internal combustion engine (ICE) vehicles have transmissions that make up a large portion of the vehicle’s weight. Lightyear was able to improve efficiency by minimizing the weight of the drivetrain. 

Electromagnetic simulations were used to determine how best to control the battery management system, solar panels, and in-wheel motors. Engineers were able to strategically determine the control system and how it deploys, stores, and distributes power most efficiently, by using simulation and optimization tools. 

One of the other key differences between EVs and ICE-powered vehicles is the amount of waste heat. An ICE loses approximately a third of its energy to heat, and that’s often used to help heat the cabin and to warm other systems and electronics, in order to keep them functioning. In an EV, there is very little waste heat, and Lightyear has an entire team dedicated to maintaining the temperature in the required ranges for various components, given the lack of engine waste heat. 

Thermal simulation techniques can be used to not only determine where heat will dissipate and how components will transfer heat to one another, but it also allows for engineers to report on the operating temperature of other components. The thermal team can use simulation to report back to other design teams about changes required in order to meet operating temperatures. In addition, climatic wind tunnels were used to determine if the proposed and simulated solutions worked when the vehicle was subjected to freezing temperatures, ice, and snow. 

Simulation Technology is Crucial to Sustainable Vehicles

The shift to fully electric fleets is well underway. Those who are already ambitiously pursuing efficient, responsible, green technologies, like Lightyear, are ahead of the curve. The need to embrace simulation technologies, in order to accelerate development cycles and produce better solutions is now critical. And it’s precisely this example, of thinking differently than the industry standard, that will help the engineering community to move towards what is best for the planet. 

About the sponsor: Ansys

Ansys provides engineering simulation software used to predict how product designs will behave in real-world environments. Founded in 1970, Ansys employs more than 4,400 professionals, many of whom are expert M.S. and Ph.D.-level engineers in finite element analysis, computational fluid dynamics, electronics, semiconductors, embedded software, and design optimization.