Electric/Hybrid Fleet Charging and Energy Management Automation

Managing a mixed fleet of electric and hybrid construction machinery introduces a complex operational variable: energy. The custom automation workflow we architect eliminates the manual burden of monitoring battery states, scheduling charging, and deciding which asset to deploy. It directly attacks the total cost of ownership by optimizing against real-time electricity rates, project demand schedules, and diesel fuel costs. The system ingests telemetry from machines, grid pricing APIs, and project management tools to make continuous, cost-minimizing decisions that protect project timelines while reducing energy spend by 15-25%.

Implementation requires integrating with asset telematics (like Samsara or Geotab), on-site charger management systems, and project software such as Procore or Oracle Primavera. The orchestrator, built on frameworks like LangGraph, executes decision logic that factors in battery health, charger availability, and job criticality. Critical controls include human-in-the-loop approval gates for major schedule deviations and a monitoring layer that tracks actual vs. projected energy costs, ensuring the system adapts to real-world site conditions and provides a defensible ROI.

This workflow automates the complex trade-off between project demands, electricity rates, and battery health across a dispersed fleet. It continuously ingests telemetry on state-of-charge, job site schedules from Primavera P6 or Procore, and real-time utility pricing feeds. An orchestration agent then schedules charging for electric assets during off-peak hours and optimizes the daily deployment of electric versus diesel machinery based on energy cost per productive hour. This directly reduces operational expenditure by 15-25% and lowers Scope 1 emissions by intelligently leveraging grid carbon intensity data.

Implementation requires integrating the orchestration layer with CMMS (IBM Maximo), telematics platforms, and utility APIs. The architecture must include approval gates for major schedule changes and real-time observability dashboards to monitor cost savings and fleet readiness. Exception handling routes charging failures or schedule conflicts to fleet managers, while the system continuously retrains its optimization models based on actual energy consumption and project outcomes, ensuring the automation adapts to seasonal and site-specific variables.

This workflow automates the complex trade-off between project demands, electricity rates, and battery health. It ingests real-time telemetry on state-of-charge, site schedules from Primavera P6 or Microsoft Project, and utility pricing feeds. An orchestration agent then schedules charging during off-peak periods, prioritizes machines for critical tasks, and may even dispatch stored battery power back to the grid during peak pricing events. The operational upside comes from slashing energy expenses by 15-25%, reducing diesel dependency, and ensuring electric assets are mission-ready without manual oversight.

Implementation requires integrating with machine telematics, building APIs to charge controllers, and connecting to utility demand-response programs. The architecture must include approval gates for high-stakes grid interactions and robust monitoring for battery degradation. Rollout is sequenced by site, with digital twin simulation used to validate logic before physical deployment. This custom build transforms energy from a fixed cost into a dynamically managed operational lever, directly protecting project margins and sustainability targets.

This workflow automates the critical bottleneck of manually managing charging schedules and asset deployment for electric and hybrid construction fleets. The operational upside comes from reducing peak-demand energy charges by 15-25% through intelligent, rate-based charging, and from optimizing the use of higher-cost diesel assets only when necessary. Implementation requires integrating battery state-of-charge telemetry from machines, real-time electricity pricing APIs, and project demand schedules from systems like Oracle Primavera P6 to drive orchestration logic.

The architecture is built on an orchestrator, often using LangGraph or a custom microservice, that ingests these disparate data streams. Controls are essential: human approval gates for major schedule overrides, continuous monitoring of charging infrastructure health, and rollback procedures for failed updates. Governance includes audit trails for carbon credit reporting and validation against utility contracts. Rollout must be sequenced by site or machine type, with digital twin simulation used to validate logic before field deployment to prevent project disruption.