Linköping, Östergötland County, Sweden
Performance and safety assessment of articulated heavy vehicles using traffic data and simulation Supervisors: Dr. Sogol Kharrazi, Prof. dr. Erik Frisk Thesis: https://liu.diva-portal.org/smash/record.jsf?pid=diva2%3A2012279&dswid=2362 Key Partners: Volvo Trucks, Chalmers University (REVERE Lab), Goodyear, Provinn 1. High-Capacity Transport (HCT) Performance Analysis Performance Assessment: Conducted large-scale analysis of Naturalistic Driving Data (NDD) for Long Combination Vehicles (LCVs), specifically A-double and DuoCAT configurations, to evaluate operational safety. Feature Engineering: Developed automated algorithms to extract and classify complex driving scenarios (lane changes, roundabouts, and intersections) from raw sensor data. Safety: Benchmarked vehicle stability and high-speed tracking performance against Performance-Based Standards (PBS) to support the transition to longer, more sustainable freight transport. 2. Active Safety & Simulation Virtual Prototyping: Built and validated a high-fidelity tractor-semitrailer model within the CARLA autonomous driving simulator, correlating virtual performance with real-world measurement data. Algorithm Development: Designed a novel 2D Time-to-Collision (TTC) surrogate safety measure, enabling the detection of simultaneous lateral and longitudinal conflicts in articulated vehicles. Validation: Executed edge-case simulation scenarios in CARLA to test collision avoidance logic and safety metrics. 3. Sensor Fusion & Computer Vision Perception Systems: Engineered a computer vision framework to track and estimate the state (position/velocity) of surrounding traffic using vehicle-mounted cameras. Localization & Fusion: Developed a robust sensor fusion model integrating low-cost GPS and IMU data to enhance the ego-vehicle’s state estimation. Behavioral Analysis: Quantified surrogate safety measures (Time Gap, TTC) during dynamic maneuvers to evaluate the interaction between heavy vehicles and passenger traffic.
1. Control Engineering 2. Powertrains 3. Engineering Optimization
Improved accuracy of tire obstacle enveloping model University Supervisors: Dr. I.J.M. Besselink and Prof. Henk Nijmeijer • Identification of the shortcomings of the previously developed tandem cam model. • Development of a new model based on the concepts of tire mechanics. • Integration of the new model in the commercial MF-Swift tire modeling software.
Influence of the tire temperature and velocity on vehicle dynamics University Supervisor: Dr. I.J.M. Besselink • Theoretical analysis of the effect of the tire temperature on vehicle behavior. • Analysis of temperature-velocity model (TVx) developed by Siemens. • Integration of the TVx model with the CarSim vehicle model using the Simulink interface. • Numerical simulations in CarSim with ISO specified manoeuvres to understand the effect of tire temperature and velocity on the vehicle handling response.
Leading a race car team of forty members for an International Competition, Formula Student Bharat and focus on managing the entire team financially and technically by meeting all the deadlines of the Competition.
1. Designed an exhaust system containing Runners and Muffler for a high performance four cylinder engine with an aim of decreasing noise and back pressure. 2. Designed a light driveline with topology optimized parts with increased durability and reliability. 3. Performed analysis to extract maximum power and torque from the engine and reduce the transmission losses. 4. Studied intriguing models such as Pacejka Model, Quarter car model and Bicycle model by interpreting tire data. 5. Kinematically and dynamically optimized Suspension parameters such as Caster, Camber , Toe, Ride height etc to increase dynamic stability. 6. Designed and optimized topology of various parts such as Uprights, Hubs etc.
Experimental studies and analysis on coated uprights using ANN and Fuzzy Logic • Employed neuro-fuzzy hybridization approach to analyze the influence of coating parameters on hardness. • Determined the optimum coating thickness and hence the hardness based on the conclusions of theoretical study. • Performed simulations and measurements with the optimum thickness to validate the theoretical results.