Data Preprocessing Services

We enhance data quality through noise reduction and normalization for accurate analysis and insights.

Noise Reduction Techniques

An electric vehicle charging plug is inserted into a charging port. The background features a vehicle with a blue surface, typically part of an electric car. A focus on modern technology and sustainable energy is evident.

Eliminating measurement errors for reliable battery management system data and improved performance.

A white electric SUV is parked in a designated parking space within an indoor garage. The vehicle is plugged into a wall-mounted electric vehicle charging station with a coiled black cable. The garage has white walls with black parking numbers visible.

A modern electric vehicle charging station is prominently displayed with the branding 'EV Power' and a capacity of 150kW. The charger features a digital screen and contactless payment options. In the background, an electric car is partially visible under a canopy.

Data Normalization Process

Standardizing time-series data to ensure consistency and accuracy in analysis and reporting.

Enhancing Data Quality

Comprehensive data preparation

Data Processing

Comprehensive data collection and pre-processing for battery analysis.

Data Normalization

Eliminating errors and standardizing time-series data effectively.

Noise Reduction

Applying techniques to enhance data accuracy and reliability.

Data-Driven Solutions

We specialize in comprehensive data collection and analysis for electric vehicle battery management systems and operational efficiency.

Close-up view of an electric vehicle charging port with a charging cable plugged into it. The port is labeled with the letters 'Z.E.' and is set against a smooth, dark-colored surface with a glossy finish.

A white electric vehicle is parked and connected to a yellow charging cable. The car's side mirror and the charging port are clearly visible and the car is located in an outdoor setting with greenery in the background.

Multi-source data collection, fusion analysis and modeling solve the pain points of battery systems in terms of performance, life, safety and cost. The specific value includes:

Performance optimization: improving energy density, charging and discharging efficiency and driving range;

Life extension: reducing battery degradation through precise management;

Safety assurance: real-time warning of risks such as thermal runaway and short circuit;

Cost control: optimizing resource allocation in production, maintenance and recycling.

Data-driven solutions are transforming from "auxiliary tools" to "core competitiveness" of electric vehicle battery systems. By connecting the entire chain of data from design, manufacturing, use, and recycling, companies can achieve an upgrade from "experience-driven" to "data intelligence," ultimately driving breakthroughs in electric vehicle endurance, safety, and cost. In the future, with the deep integration of 5G, edge computing, and AI technologies, the data value of battery systems will be further released, becoming a key engine for the transformation of the new energy vehicle industry.