Design & Optimization for Vehicle Dynamic Events of Electric 2-Wheeler Using Genetic Algorithm Approach 2024-26-0260

The drive of Electric vehicles gained lot of traction in two-wheeler market, customer preferences and affordability are major reasons leaning towards electric 2 wheelers. As the two-wheeler market is huge, product development timelines are very sensitive to capture the market. Simulation based approaches are gaining lot of traction among manufacturers helping them to optimize the performance and production cycle time. During the design phase, hard points of the vehicle need to be defined. A multi body dynamic simulation approach will be made to evaluate the vehicle’s performance with initial design of hard points. Based on the ride and handling results, hardpoints optimization will be set up using Design of Experiments (DOE) studies. Suspension characteristics and sensitivities are studied to improve the ride behavior of the vehicle. A two-wheeler vehicle is a highly unstable and heavily depend on the skill of rider model. To improve the safety and handling behavior a fall detection and self-balancing mechanism can be designed and simulated using multibody simulation tools with Genetic Algorithm approach (GA). A specific ISO event identified to simulate the design parameters for balancing the vehicle with right Proportional Integral Derivative (PID) tuning based on the mass imbalance, counter balancing signals will be applied to stabilize the vehicle while maneuverings and help to improve the driving pattern to make a better handling characteristics and safety of the vehicle.