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Important: This Guidance requires the use of Amazon Forecast, which is no longer available to new customers. Existing customers of Amazon Forecast can continue using and deploying this Guidance as normal.
This Guidance shows how to create a battery digital twin, a virtual representation of a physical electric vehicle battery or battery energy storage system (BESS), and overlay real-time data such as voltage, current, and temperature. This integrated visual representation (the digital twin) enables data processing and analytics for insights into the battery's past, current, and future states, including electrical, thermal, and aging behavior. Using these insights, you can monitor battery health more accurately, predict outcomes, and optimize operations for improved performance, reliability, and safety through visualization, fault detection models, and early issue identification.
Please note: [Disclaimer]
Architecture Diagram

[Architecture diagram description]
Step 1
The vehicle sends telemetry data, such as operating voltage, current, temperature, and cell-level data, to AWS IoT Core.
Step 2
An AWS IoT rule differentiates data based on whether the data is required for real-time analytics or batch analysis.
Step 3
Amazon Kinesis Data Streams and Amazon Managed Service for Apache Flink ingest telemetry data for diagnostic trouble code (DTC) detection. AWS Lambda initiates the pre-processing job in AWS Glue to transform battery health data into csv format.
Step 4
Real-time telemetry data, such as current, temperature, and charge data, is sent to Amazon Timestream for threshold model detection. Batch data is sent to Amazon Simple Storage Service (Amazon S3) for anomaly model training, and Amazon DynamoDB stores metadata.
Step 5
AWS Glue pre-processes data by adding context to data stored in Amazon S3. AWS Glue post-processes timeseries data to visualize in the frontend application. Amazon EventBridge orchestrates the event workflow for model prediction.
Step 6
Amazon Forecast predicts the state of health of the battery using a pre-trained model. Amazon SageMaker trains a prediction model based on the batch battery data in Amazon S3.
Step 7
AWS Amplify deploys and hosts the frontend application. AWS AppSync enriches data using custom data sources. Amazon API Gateway manages APIs securely.
Step 8
Original equipment manufacturers (OEMs) and electric vehicle owners can access this application securely through API Gateway.
Well-Architected Pillars

The AWS Well-Architected Framework helps you understand the pros and cons of the decisions you make when building systems in the cloud. The six pillars of the Framework allow you to learn architectural best practices for designing and operating reliable, secure, efficient, cost-effective, and sustainable systems. Using the AWS Well-Architected Tool, available at no charge in the AWS Management Console, you can review your workloads against these best practices by answering a set of questions for each pillar.
The architecture diagram above is an example of a Solution created with Well-Architected best practices in mind. To be fully Well-Architected, you should follow as many Well-Architected best practices as possible.
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Operational Excellence
Amazon CloudWatch provides centralized logging, monitoring, and alerting services for operational anomalies and model drift detection. API Gateway securely exposes APIs for external models, while Lambda offers a serverless, scalable, and highly available platform. It automatically scales resources based on demand, reducing manual capacity planning and infrastructure management overhead.
This serverless approach allows users to focus on application logic while AWS handles the underlying infrastructure, helping to ensure operational excellence through automation, fault tolerance, simplified deployment, and automatic scaling.
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Security
AWS Key Management Service (AWS KMS) secures data through encryption and key management, and AWS Identity and Access Management (IAM) implements the principle of least privilege. By leveraging these integrated services, you can mitigate risks, protect sensitive data, and improve the overall security posture of your AWS infrastructure.
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Reliability
AWS services like Lambda, Amazon S3, and EventBridge enhance application reliability through their robust and scalable architectures. Lambda auto scales functions for availability, Amazon S3 provides durable and redundant data storage, and EventBridge delivers a reliable event-driven integration platform.
These services enable you to build resilient applications that withstand failures, help ensure data protection, and facilitate seamless component communication. By adopting these services, you can benefit from fault-tolerant infrastructure, automatic scalability, and managed services that reduce operational overhead.
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Performance Efficiency
Forecast provides accurate predictions for optimized resource allocation, and EventBridge enables responsive, high-performance applications that react quickly to changing conditions. AWS IoT FleetWise collects and analyzes vehicle data at scale to monitor and improve fleet performance. Together, these services empower organizations to proactively address bottlenecks, make informed decisions, and optimize the efficiency of their cloud-based solutions and connected systems.
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Cost Optimization
Lambda and AWS Glue charge only for resources used, while Amazon S3 and Timestream provide cost-effective storage and data processing capabilities that adjust to usage patterns. By using these services, you can avoid infrastructure management overhead, align cloud spending with actual resource consumption, and achieve significant cost savings.
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Sustainability
Workloads with gigabytes of historic data benefit from the flexibility to more sustainably store or archive data at energy-efficient data centers, helping to align with environmental goals while maintaining data availability. Amazon S3 Intelligent Tiering helps promote sustainability by automatically moving data between storage tiers based on access patterns, optimizing energy usage.
Frequently accessed data is stored in the low-latency frequent access tier, while less frequently accessed data resides in the more energy-efficient infrequent access and archive access tiers. This lifecycle management approach helps enable you to minimize the environmental impact of your cloud storage infrastructure without compromising performance or data accessibility.
Implementation Resources

The sample code is a starting point. It is industry validated, prescriptive but not definitive, and a peek under the hood to help you begin.
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Disclaimer
The sample code; software libraries; command line tools; proofs of concept; templates; or other related technology (including any of the foregoing that are provided by our personnel) is provided to you as AWS Content under the AWS Customer Agreement, or the relevant written agreement between you and AWS (whichever applies). You should not use this AWS Content in your production accounts, or on production or other critical data. You are responsible for testing, securing, and optimizing the AWS Content, such as sample code, as appropriate for production grade use based on your specific quality control practices and standards. Deploying AWS Content may incur AWS charges for creating or using AWS chargeable resources, such as running Amazon EC2 instances or using Amazon S3 storage.
References to third-party services or organizations in this Guidance do not imply an endorsement, sponsorship, or affiliation between Amazon or AWS and the third party. Guidance from AWS is a technical starting point, and you can customize your integration with third-party services when you deploy the architecture.