With the rapid expansion of battery applications for electric vehicles (EVs), energy storage systems (ESS), consumer electronics, and more, the demand for battery development and validation continues to grow. Battery laboratories handle massive amounts of charge/discharge test data every day. Different cell types and development stages may be tested simultaneously across various Chroma battery test systems (e.g., 17010 series), resulting in dispersed data sources and inconsistent formats. Engineers often spend significant time consolidating information, leading to inefficient and error-prone workflows.
Chroma 17092 Data Spectrum was developed specifically to address these challenges. Purpose-built for battery test data analysis, it provides an all-in-one software solution featuring cross-system data integration, fast search, advanced visualization, flexible reporting, and professional analysis tools. This enables engineers to efficiently turn complex data into actionable insights, accelerating both R&D and QA decision-making.
With Data Spectrum, users can compare and analyze data from multiple systems on a single platform. Its highly customizable charting and reporting tools make complex test data easy to interpret. R&D engineers can quickly compare cycle life curves of different battery recipes, QA engineers can generate daily production line inspection reports based on preset filters with one click.
Data Spectrum features a multilingual interface (English, Traditional/Simplified Chinese), making it suitable not only for R&D labs but also for global production lines and cross-border teamwork. Enabling unified data management and analysis across R&D, mass production, QA, and long-term reliability validation, Data Spectrum accelerates time-to-insight, shortens battery development cycles, and strengthens quality management.
Direct Data Access × Precise Filtering × Simplified Fields - Quick Start for Analysis
Data Spectrum offers efficient data access and management. By simply installing the software on a PC, users can connect directly to the database and retrieve the latest test data across all systems in real time. A unified test record list displays all systems, projects, and channel data, and supports multi-condition filtering by channel number, DUT model, or test plan—making it easy to locate the desired data for focused analysis.
In the past, engineers had to export files from each tester and manually merge them for evaluation. Data Spectrum streamlines this process by eliminating repetitive tasks and letting engineers jump straight into analysis. This not only saves valuable time but also reduces the risk of human error.
The Field Template feature allows users to customize which fields are shown: field names and units can be edited and saved into templates for reuse, enabling engineers to focus only on relevant data. The interface becomes cleaner, memory usage is lower, and time spent filtering large datasets is significantly reduced.
Once target data is identified, engineers can further narrow down the range using conditions such as recipe, step, cycle, or loop, retaining only data relevant to the analysis.
Data Spectrum integrates the "data retrieval→filtering→ simplification→analysis" pipeline into one seamless process, delivering a fast, efficient, and intuitive data analysis experience.
Graphical Data Visualization - Insight at a Glance
Engineers often need to compare performance under different test conditions. Traditional tools require heavy configuration and manual comparison, making the process cumbersome and time-consuming.
Data Spectrum provides intuitive charting tools with support for multi-axis plotting (up to 4Y + 1X). It can simultaneously display voltage, current, capacity, and impedance, enabling users to observe trends at a glance. Built-in functions like curve comparison and cycle overlay allow users to directly select data and conditions to instantly visualize and compare test outcomes. Whether it's capacity fade, rate performance, or high-temperature performance, engineers are empowered to reach conclusions intuitively and efficiently.
Key Benefits:
• Reduces repetitive tasks to make cross-project comparisons more efficient and clear.
• Results are presented in a clear, visualized way so differences can be seen at a glance and decisions become more intuitive.
▲ Multi-axis plotting
▲ Curve comparison
Chart replication & Overlay Analysis - Smart Comparison
Data Spectrum includes built-in chart copy and overlay analysis functions. Users can set up a chart once and reuse it across multiple datasets. Data from different projects or batches can be overlaid onto a single chart for instant visual comparison.
Use Case: An R&D engineer can set up a chart for a rate test and reuse it for other data without readjusting axes or styles. During cross-project analysis, performance curves from different batches can be overlaid for quick comparison.
Key Benefits:
• Reduces repetitive setup, improves cross-project analysis efficiency and clarity.
• Results are visualized clearly, enabling quick understanding of differences and intuitive decision-making.
▲ Chart replication
▲ Overlay analysis
Engineers often need to compile charts, tables, and data into reports. Traditional methods require switching between Excel and Word and adjusting layouts manually, which easily causes inconsistencies in data.
Data Spectrum provides a highly customizable report editor, allowing users to drag and drop charts and tables, define layouts, and quickly produce project reports, QA reports, or weekly summaries. Frequently used templates can be saved and reused to reduce preparation time.
Chart components and analysis plans can be archived and organized. Each chart and plan can be named, categorized, and reused later, eliminating redundant setup. Last but not least, chart components include built-in traceability: clicking a chart can link back to the raw test data, which ensures all contents are verifiable and increases the credibility of analysis results.
Key Benefits:
• High efficiency → Reuse report templates to complete production quickly.
• Traceability → Chart elements correspond to the original data to ensure consistent results.
• Centralized management → Archive analysis plans and charts to reduce rework.
