EV Platform Architecture


A modern EV platform is a cyber-physical system: energy storage, power electronics, thermal loops, sensors, networks, compute, and the software layers that coordinate them. In a software-defined vehicle (SDV), the platform becomes a programmable substrate where control, diagnostics, autonomy, and over-the-air (OTA) updates run across a unified architecture.

This page focuses on the software-defined and compute layers of the vehicle platform as part of the broader Software-Defined Systems (SDS) stack.


Core Architectural Elements of a Software-Defined Vehicle Platform

1. Central Vehicle Compute

  • Executes multi-domain workloads across ADAS, powertrain, body, and energy domains.
  • Integrates accelerators (GPU, NPU, DSP) for neural-network inference and perception.
  • Implements safety islands, lockstep cores, and hardware redundancy for fail-operational behavior.
  • Supports partitioned workloads for autonomy, perception, and real-time control loops.

2. Zonal Vehicle Architecture

  • Replaces many discrete ECUs with zonal controllers grouped by physical location in the vehicle.
  • Uses an automotive Ethernet backbone (for example 100/1000BASE-T1) between zones and central compute.
  • Reduces wiring harness complexity and improves reliability and packaging.
  • Provides deterministic routing for safety-critical and latency-sensitive traffic.

3. Vehicle Operating System

  • Provides standardized abstractions for sensors, actuators, and network interfaces.
  • Combines real-time OS segments for safety-critical functions with higher-level services for non-critical tasks.
  • Supports containerization or service-oriented architectures for application software.
  • Manages update and rollback behavior across partitions and modules.

4. In-Vehicle Networks

  • CAN and CAN-FD for low-latency control and legacy subsystems.
  • Automotive Ethernet for high-bandwidth ADAS, perception, and diagnostics.
  • LIN for simple actuators and comfort features.
  • Time-sensitive networking (TSN) for deterministic transport in autonomy workloads.

5. Energy & Thermal Software Layers

  • Battery management algorithms for state-of-charge and state-of-health estimation.
  • Cell balancing and protection logic under varying duty cycles.
  • Inverter and motor control loops tuned for efficiency and response.
  • Thermal orchestration across pack, drive units, power electronics, and cabin.
  • Predictive heating and cooling for charging sessions and performance demands.

6. Powertrain Control Software

  • Implements torque vectoring and traction management for different surfaces and loads.
  • Uses field-oriented control (FOC) for precise electric motor control.
  • Optimizes inverter switching strategies for silicon and silicon carbide devices.
  • Coordinates regenerative braking with friction brakes and stability control.
  • Monitors high-voltage distribution and performs fault detection and isolation.

7. Perception & Sensor Fusion (Vehicle Context)

  • Ingests multi-camera, radar, and optionally LiDAR data streams.
  • Handles sensor timestamping, synchronization, and calibration.
  • Implements early, mid, or late fusion models depending on system design.
  • Defines redundancy paths if individual sensors or links degrade or fail.

8. Autonomy Compute Stack

  • Runs inference for perception, prediction, and planning models on the vehicle.
  • Abstracts sensor inputs through unified interfaces for autonomy software.
  • Executes path planning integrated with vehicle dynamics and control limits.
  • Monitors compute health, latency, and performance for safety and quality of service.

9. Vehicle OTA Architecture

  • Uses secure boot and a hardware root-of-trust to validate firmware and software images.
  • Supports delta and full-image updates across central compute, zonal controllers, and domain ECUs.
  • Coordinates update campaigns with rollback paths to last known-good states.
  • Integrates telemetry feedback loops for update success, failures, and regression detection.

10. Safety, Redundancy & Fail-Operational Behavior

  • Implements redundant compute paths for critical functions (for example steering, braking, torque control).
  • Supports independent power domains to maintain control under partial failures.
  • Aligns with functional safety standards such as ISO 26262.
  • Integrates cybersecurity requirements (for example ISO 21434) into the architecture.

Relationship to the Broader SDS Stack

Vehicle platform architecture is one branch of the overall Software-Defined Systems (SDS) framework. The same design principles extend to software-defined robotics, infrastructure, energy systems, and industrial operations. The vehicle is often the most constrained environment, making it a useful reference for SDS patterns across the rest of the stack.




E2E Software Stack

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