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Product Management Root Cause Analysis Question: Investigating sudden battery drain in autonomous delivery vehicles
Image of author vinay

Vinay

Updated Nov 19, 2024

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Asked at Nuro

15 mins

What caused the sudden 30% increase in battery drain on Nuro's R3 vehicles during short-distance trips in Phoenix?

Problem-Solving Data Analysis Technical Understanding Autonomous Vehicles Last-Mile Delivery Electric Vehicles
Root Cause Analysis Autonomous Vehicles Product Troubleshooting Last-Mile Delivery Battery Optimization

Introduction

The sudden 30% increase in battery drain on Nuro's R3 vehicles during short-distance trips in Phoenix presents a critical issue that demands immediate attention. This analysis will systematically identify, validate, and address the root cause while considering both immediate and long-term implications for Nuro's autonomous delivery service.

To tackle this problem, I'll follow a structured approach that covers issue identification, hypothesis generation, validation, and solution development. My goal is to uncover the underlying factors contributing to the increased battery drain and propose effective strategies to mitigate the issue.

Framework overview

This analysis follows a structured approach covering issue identification, hypothesis generation, validation, and solution development.

Step 1

Clarifying Questions (3 minutes)

  • Looking at the timing, I'm thinking this could be related to recent software updates. Have there been any significant software changes deployed to the R3 fleet in Phoenix recently?

Why it matters: Software updates can inadvertently affect battery performance. Expected answer: Yes, a new navigation algorithm was implemented last week. Impact on approach: If confirmed, we'd focus on analyzing the new algorithm's impact on battery usage.

  • Considering the specificity of "short-distance trips," I'm wondering about the definition. What's the exact range we're classifying as "short-distance" for the R3 vehicles?

Why it matters: Understanding the trip length helps isolate the problem and compare data accurately. Expected answer: Short-distance trips are defined as under 5 miles. Impact on approach: This would help us analyze data for specific trip lengths and identify patterns.

  • Given the 30% increase, I'm curious about the baseline. What was the average battery drain percentage for short trips before this issue arose?

Why it matters: Establishing a clear baseline helps quantify the problem and set benchmarks for improvement. Expected answer: Previously, short trips consumed about 10% of battery charge. Impact on approach: This would allow us to calculate the exact increase and set specific goals for resolution.

  • Thinking about environmental factors, has there been any significant change in weather patterns or road conditions in Phoenix recently?

Why it matters: External factors like extreme heat or new road construction could affect battery performance. Expected answer: Temperatures have been consistent, but there's ongoing road work in some areas. Impact on approach: If confirmed, we'd investigate how road conditions might be impacting battery usage.

  • Considering potential hardware issues, have there been any recent changes or updates to the R3 vehicles' battery systems or other hardware components?

Why it matters: Hardware changes or degradation could significantly impact battery performance. Expected answer: No recent hardware changes, but batteries are approaching their first maintenance cycle. Impact on approach: This would prompt us to investigate battery health and maintenance schedules as potential factors.

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