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 errorprone 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-toinsight, 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 manual 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 capability, or high-temperature performance, engineers are empowered to reach conclusions intuitively and efficiently.
Results are presented in a clear.
Visualized way so differences can be seen at a glance and decisions become more intuitive.
Chart Copying & 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.
Results are visualized clearly, enabling quick understanding of differences and intuitive decision-making.
Report Editing & Management — Streamlined and Traceable
Engineers often need to compile charts, tables, and dates 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.
Traceability → Chart elements correspond to the original data to ensure consistent results.
Centralized management → Archive analysis plans and charts to reduce rework.
DVA Curve Transformation & Characteristic Peak Identification
In battery charge-discharge curves, subtle changes caused by electrode reactions are often masked by the overall voltage trend. Observing only the raw voltage–capacity curve often makes it difficult to quickly distinguish differences across different cycles, samples, or test conditions. The DVA Toolbox converts voltage and capacity data into dV/dQ curves, amplifying reaction characteristics in a non-destructive manner, making subtle curve variations easier to identify.
Users can directly select charge/discharge steps, set X/Y-axis fields (such as capacity and voltage) and analysis range, then generate dV/dQ data using either numerical differentiation or linear regression based on data characteristics. The system retains analysis conditions and curve settings, allowing users to maintain a consistent analysis approach when switching to other cycles or samples, reducing repetitive data preparation and plotting.
Once the curve is generated, the tool can identify peak and valley points while allowing users to adjust marker positions, converting each reaction region into traceable feature points. Concurrently, users can designate starting and ending peaks for automatic calculation of peak-to-peak capacity, with synchronized graphical and tabular displays.
The DVA Toolbox integrates Data Selection → Curve Transformation → Peak Identification → Peak-to-Peak Capacity Calculation within a single tool. Engineers do not need to dismantle batteries or repeatedly convert files between multiple software programs, allowing them to proceed more quickly to comparison and interpretation.
Integrated Operation → Centrally manage analysis settings, curves, and tables.
Result Quantification → Support further comparison using peak positions and peak-to-peak capacity.
Peak-to-Peak Capacity & Condition Comparison
The DVA not only displays curve shapes; it converts key differences into comparable numerical values. Engineers can observe the location, shape, and relative shifts of characteristic peaks to identify reaction differences across different cycles, samples, C-rates, or temperature conditions.
By defining analysis intervals using starting and ending peaks, the DVA Toolbox automatically calculates the peak-to-peak capacity for each curve, reducing errors associated with manual reading and tabular data entry. With a benchmark curve for comparison, users can further compare capacity differences and change rates to quickly identify curves with more pronounced changes.
This feature is suitable for evaluating cycle life, C-rates, temperatures, samples, or process conditions. Applying the same peak definitions and analysis ranges across different conditions establishes a consistent basis for comparison and reduces differences caused by variations in interpretation among users. Analysis graphs, peak points, and capacity tables can be viewed simultaneously, with support for copying to Excel or exporting for record-keeping, helping keep curve interpretation, numerical verification, and report preparation consistent.
▲ Reduce manual calculation and transcription errors to quickly compare electrode degradation differences
Reference Curve × Multi-Curve Comparison: Quickly Identify Changes in Characteristic Peaks
DVA Tool supports reference curve and multi-curve comparison. Users can load a previously marked curve as a reference curve, adjust its position using scale adjustment, horizontal shift, and curve inversion, and then map existing characteristic peaks onto new curves—reducing the time spent finding and marking peaks for every analysis.
Multiple DVA curves can be overlaid on a single chart to compare peak shifts, curve shapes, and changes in peak-to-peak capacity across different cycles, samples, C-rates, or temperatures. Simultaneously displaying reference and comparison curves makes trends and discrepancies easier to interpret.
Compare multiple curves in a single chart to speed up anomaly and trend identification.
Peak-to-Peak Capacity Comparison & Result Export
In cycle life or condition comparisons, engineers can select one curve as the benchmark and add multiple comparison curves to calculate peak-to-peak capacity using the same starting and ending peaks. The system automatically compiles each curve's peak-to-peak capacity, difference, and rate of change, displaying them simultaneously in graphical and tabular formats, reducing item-by-item calculations and manual comparison.
After the analysis is complete, users can export the analysis conditions, raw X/Y-axis data, calculated dV/dQ data, peak points, peak-to-peak capacities, rates of change, and analysis graphs. The data is organized into separate tabs for convenient review in Excel, report preparation, or integration with other test results.
All analysis configurations and results can be retained within the same workflow. Engineers can trace the specific test steps, data ranges, curve settings, and peak markers used in the analysis, ensuring that the basis of the analysis remains clear when reviewed by different users or at a later time.
Complete Export → Organize charts and data together.
Traceability → Preserve analysis conditions and results consistently.
