Autonomous Driving Thermal Management for Multi-GPU Inference

Overview of Technical Issues:

When multiple GPUs operate simultaneously for autonomous driving inference, the cooling structures and heat transfer pathways provide insufficient heat removal capacity, causing GPU temperatures to exceed safe operating limits and triggering thermal throttling or protective shutdowns that compromise inference performance and autonomous driving system reliability; the goal is to achieve adequate thermal management that maintains all GPUs within optimal temperature ranges during sustained high-performance inference operations.

Solution directions generated for this problem

Problem Direction 1 :

ImproveCoolant flow velocity
VS
ConstraintCooling system power consumption

Inspiration 1 : Cross-domain reference

Application Principle: #2 Taking out (Extraction)
Cross-domain applicability Assess applicability
Hydraulic control device and construction machine with same
Innovative Solution Refine solution

External vehicle-integrated heat rejection for GPU thermal management

Route GPU heat externally to vehicle systems
How to solve :
  • Extract GPU waste heat from compute enclosure by routing coolant lines to vehicle HVAC radiator or underbody heat exchanger, rejecting 2000-3000W total load externally
  • Install compact micro-channel cold plates (6-8mm thickness, copper base with 0.4mm channel width) directly bonded to each GPU die using graphene-enhanced thermal paste (≥8 W/(m·K) conductivity, 0.1mm bond-line thickness)
  • Operate low-pressure coolant loop at 0.8-1.2 L/min per GPU using variable-speed pump (120-180W power range), with coolant pre-conditioned to 35-40°C by vehicle radiator before entering GPU cold plates
Expected Effect : Junction temp 72-78°C, pump power ≤180W, thermal resistance 0.06-0.08°C/W, no internal volume increase
Risk Control :
  • vehicle radiator capacity margin insufficient during summer peak ambient
  • coolant line routing complexity and leak risk in automotive vibration environment
  • thermal coupling between GPU loop and cabin HVAC affecting passenger comfort

Problem Direction 2 :

ImproveHeat sink effective thermal conductivity
VS
ConstraintCooling system volume

Inspiration 1 : Cross-domain reference

Application Principle: #7 Nested doll (Nesting)
Cross-domain applicability Assess applicability
Reversing bend
Innovative Solution Refine solution

Nested micro-channel cold plate with integrated vapor chamber for GPU thermal management

Embed micro-channel cold plate (5mm thick) directly into GPU substrate, nesting within existing package height to achieve 0.06-0.07°C/W thermal resistance without external volume growth
How to solve :
  • Integrate sintered copper vapor chamber (0.8mm thick, wick porosity 55-65%) between GPU die and micro-channel layer, using capillary action to spread 300-500W heat load uniformly across 80×80mm area
  • fabricate parallel micro-channels (0.6mm width, 2mm depth, 0.4mm wall thickness) via precision CNC milling in copper substrate, achieving ≥200 W/(m·K) effective thermal conductivity with coolant velocity 0.8-1.2 m/s at 150W pump power
  • bond vapor chamber to micro-channel base using vacuum brazing at 780-820°C under ≤10⁻⁴ Pa atmosphere, ensuring <0.01°C/W interface resistance — total assembly thickness 6.5mm fits within original 8mm GPU package envelope
Expected Effect : Thermal resistance 0.06-0.07°C/W (60% reduction); GPU junction temp 72-78°C; zero external volume increase; cooling power maintained at 150W
Risk Control :
  • vapor chamber wick delamination under thermal cycling
  • micro-channel clogging from coolant particulates
  • brazing void formation exceeding 5% bond area

Problem Direction 3 :

ImproveCooling system heat removal capacity
VS
ConstraintCooling system volume

Inspiration 1 : Cross-domain reference

Application Principle: #1 Segmentation
Cross-domain applicability Assess applicability
Multi-pole electrical protection system and electrical equipment including the system
Innovative Solution Refine solution

Modular distributed micro-loop cooling architecture for multi-GPU thermal management

Partition the 2000-3000W total heat load into independent micro cooling modules, each GPU assigned a dedicated 300-500W compact loop with local micro-pump (15W) and thin-profile cold plate (8mm thickness, 0.07°C/W thermal resistance);Distribute modules spatially across available enclosure surfaces—mount micro-radiators (60×80×12mm each) on enclosure walls, floor, and lid using vehicle structure as heat sink, eliminating centralized bulky radiator;Parallel hydraulic architecture with isolated loops prevents cross-contamination, enables independent flow control (0.8-1.2 L/min per loop), and allows incremental scaling—total pump power 120W (8 modules × 15W) vs 400-500W for single high-capacity system
How to solve :
  • Volume increase ≤18% vs 40-60% baseline
  • thermal resistance 0.07°C/W
  • GPU junction temp 76-79°C
  • total cooling power 120W
Expected Effect : micro-pump reliability under vibration;cold plate bonding thermal fatigue;flow balancing across distributed loops
Risk Control :
  • 1

Problem Direction 4 :

ImproveCooling system heat removal capacity
VS
ConstraintCooling system power consumption

Inspiration 1 : Cross-domain reference

Application Principle: #2 Taking out (Extraction)
Cross-domain applicability Assess applicability
System, method, and aparatus for extracting power from a photovoltaic source of electrical energy
Innovative Solution Refine solution

Passive heat pipe network with vehicle body panel heat rejection

Passive heat transport eliminates active cooling power
How to solve :
  • Install large-diameter heat pipes (12–18mm) from each GPU to vehicle roof/side panels, transferring 300–500W per GPU via passive evaporation-condensation cycle with zero electrical power consumption
  • Use sintered copper wick heat pipes with thermal conductance ≥200 W/K, operating fluid R134a or ammonia, evaporator section bonded to GPU cold plate with <0.05°C/W interface resistance
  • Vehicle body panels serve as passive condensers with total area 0.8–1.2 m², rejecting 2000–3000W total load through natural convection and radiation at 60–70°C surface temperature, maintaining GPU junction temperature at 75–80°C
Expected Effect : 2000–3000W heat removal at 0W active power; cooling power reduced from 400–500W to 0W; system efficiency gain 15–20%
Risk Control :
  • heat pipe orientation sensitivity in vehicle motion
  • condenser panel temperature variation with ambient conditions
  • heat pipe working fluid charge optimization

Problem Direction 5 :

ImproveCoolant flow velocity
VS
ConstraintMust not deteriorate

Inspiration 1 : Cross-domain reference

Application Principle: #10 Preliminary action
Cross-domain applicability Assess applicability
Method and apparatus for the manufacturing of biochar with thermal treatment
Innovative Solution Refine solution

Pre-chilled thermal buffer reservoir with phase-change material for GPU cooling

Pre-cool thermal buffer during idle periods
How to solve :
  • Install a thermal buffer reservoir containing 8-12 kg phase-change material (PCM) with melting point 18-22°C, pre-chilled to 10-15°C during vehicle idle using 80W auxiliary cooling
  • During inference bursts, route coolant through PCM reservoir where latent heat absorption (≥200 kJ/kg) removes 300-500W per GPU at moderate flow velocity 1.5-2.0 m/s, avoiding high-velocity 3.5-4.5 m/s pumping
  • Implement dual-mode pump control: 150W gentle circulation during PCM charging phase, 200W moderate flow during discharge phase—eliminating 400-500W continuous high-speed operation while maintaining GPU junction temperature 75-80°C.
Expected Effect : Flow velocity reduced 45%, pump power reduced 50-60%, cavitation risk eliminated, thermal performance maintained
Risk Control :
  • PCM thermal cycling degradation after 2000-3000 cycles
  • reservoir volume integration in compact enclosure
  • PCM melting point shift ±3°C affecting buffer capacity
Patsnap Eureka Solution