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Welcome back to the Tech Heads F1 podcast! This week Bryson and Molly sit down with engineer and technical maven Mirco Bartolozzi, better known as @F1DataAnalysis. When Mirco isn't developing complex vehicle dynamics models a PhD student, he spends his time performing analysis on the data generated by Formula 1 and helping to explain its most complex aspects in a clear, intelligible way. We begin our discussion with how Mirco first discovered his passion for motorsport and what makes F1 so unique for fans of a technical bent. We proceed to cover a wide range of other topics, including data driven performance estimation, kinematics for non-engineers, reverse-Ackermann steering and the full solution to a clever conceptual problem Mirco posted on Twitter recently. This was such a great conversation, we hope you enjoy it!
Mirco Bartolozzi Intro (1:32)
Hosts:
"The Most Powerful Part of an F1 Car"
"Computing Gear Ratios"
"Reverse-Ackermann Steering Geometry"
"Example of a Convex Hull Bounding Acceleration Data"
By Tech Heads F15
1616 ratings
Welcome back to the Tech Heads F1 podcast! This week Bryson and Molly sit down with engineer and technical maven Mirco Bartolozzi, better known as @F1DataAnalysis. When Mirco isn't developing complex vehicle dynamics models a PhD student, he spends his time performing analysis on the data generated by Formula 1 and helping to explain its most complex aspects in a clear, intelligible way. We begin our discussion with how Mirco first discovered his passion for motorsport and what makes F1 so unique for fans of a technical bent. We proceed to cover a wide range of other topics, including data driven performance estimation, kinematics for non-engineers, reverse-Ackermann steering and the full solution to a clever conceptual problem Mirco posted on Twitter recently. This was such a great conversation, we hope you enjoy it!
Mirco Bartolozzi Intro (1:32)
Hosts:
"The Most Powerful Part of an F1 Car"
"Computing Gear Ratios"
"Reverse-Ackermann Steering Geometry"
"Example of a Convex Hull Bounding Acceleration Data"

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