Error Management
A happy story of how I solved unhappy scenarios for EVBox - Liviqo
*The contents of this case study have been modified to protect the privacy of EVBox. Featuring only publicly available product components, it showcases my process while preserving the confidentiality of all research and data owned by the company
Timeline
Approximately 3 months
Employer
EVBox
Role
UX Designer
Sole designer on this project–led design efforts, collaborating closely with: system architects + customer support + implementation engineers + copywriters
Award
The Problem
🤝 Project Dependencies & Stakeholders identified
I had to look beyond just the design and bring in different perspectives. To make sure the solution worked not only for end users, but also for the people behind the system. I collaborated closely with:
System Architects – To understand the technical language and logic behind each error.
Customer Support Teams – To identify phone guidance users receive and embed it directly into the UI.
Implementation Engineers – To assess feasibility, align timelines, and ensure cross-version compatibility.
Copywriting Team – To craft clear, concise, and helpful error messages.
Meet Alex our user persona:
Name: Alex
Background: EV driver – could be a commuter, traveler, or fleet driver.
Emotional State at Point of Use: Varies—could be joyful, frustrated, distracted.
Needs: Clarity, Speed, Minimal hassle.
The solution is tailored for someone who doesn’t want to overthink an error and just wants to know what to do.
Ideation and collaboration
Step 1: Gathering Existing Solutions
I started by: 1. Reviewing internal support docs to map existing error communication. 2. Found only 4 generic user actions given—same for all errors, no context considered.
Step 2: Consulting System Architects and Mapping Logic to UI:
Next, I reached out to the architecture team to:
Map error codes to solution categories and user actions.
Built the foundation for a scalable, context-aware error model.
Step 3: Defining UI Patterns
I ideated on visual cues using LED colors and screen themes and ensured alignment with EV charging safety standards and protocols.
🚨 Technical Limitations I Found in the Process
It was non-touch, with limited space for content.
Any text we added had to be translated and maintained across markets.
Space constraints meant prioritising microcopy that supports quick decision-making.
The solution
What emerged was a scalable error-handling UI model that accurately reflects backend errors:
Summarises 24 system errors into 5 reusable UI patterns.
Helps users take action on the spot.
Used minimal, translated text and clear visuals.
100% aligns with support team guidance.
Testing the Solution and Feedbacks
During the testing phase, we encountered an important issue:
‼️ We discovered blinking orange LED was distracting during long charging sessions.
Users found it intrusive at night, affecting drivers, garage sharers, and neighbours.
Accessibility
Accessibility wasn’t just digital—it extended to real-world environments.
☀️ 🌒
- Outdoor Readability: Designed glare-resistant, high-contrast screens for optimal visibility in bright sunlight and adjustable brightness for eye comfort at night.
🌧️ ❄️ 🧤
- Weather-Resilient Interactions: Ensured product responsiveness in rain and with gloves—because real-world conditions aren't always perfect.
🇺🇸 🇩🇪
- Compliance: Aligned the design with CTEP standards (US) and Eichrecht regulations (Germany), ensuring readiness for deployment in two highly regulated EV charging markets.
What’s Next and Overall feedback
Tested Users found the visuals intuitive and instructions helpful.
Customer Support Teams – reported fewer repetitive calls.
System Architects – Appreciated clear mapping and reported faster issue resolution.
Engineers confirmed ease of integration in upcoming versions.