Automatic Temperature Control Systems in Vehicles

Automatic Temperature Control (ATC) systems represent closed-loop climate management architectures that maintain cabin thermal conditions at user-defined setpoints through continuous feedback, actuator modulation, and predictive compensation. These systems integrate multiple sensor inputs, apply control algorithms, and command variable-capacity HVAC components to minimize thermal error while optimizing energy consumption and occupant comfort.

Fundamental Control Architecture

ATC systems operate on a multi-input, multi-output (MIMO) control paradigm where the Electronic Climate Control Module (ECCM) processes sensor data and commands actuators to achieve thermal equilibrium between heat gains and HVAC system cooling/heating capacity.

The primary energy balance governing cabin temperature control is:

$$Q_{HVAC} = Q_{solar} + Q_{ambient} + Q_{occupant} + Q_{equipment} + m_{vent}c_p(T_{ambient} - T_{cabin})$$

Where:

• $Q_{HVAC}$ = HVAC system capacity (W)
• $Q_{solar}$ = Solar radiation heat gain (W)
• $Q_{ambient}$ = Conductive/convective heat transfer through cabin envelope (W)
• $Q_{occupant}$ = Metabolic heat generation from occupants (typically 100-120 W per person)
• $Q_{equipment}$ = Heat from electronics and powertrain (W)
• $m_{vent}$ = Ventilation air mass flow rate (kg/s)
• $c_p$ = Specific heat of air (1.006 kJ/kg·K)

graph TB
    A[Cabin Temperature Setpoint] --> B[Control Algorithm]
    C[Temperature Sensors] --> B
    D[Humidity Sensor] --> B
    E[Solar Load Sensor] --> B
    F[Ambient Temperature] --> B
    B --> G[Compressor Speed Command]
    B --> H[Blower Speed Command]
    B --> I[Mode Door Position]
    B --> J[Temperature Door Position]
    G --> K[Discharge Air Temperature]
    H --> K
    I --> K
    J --> K
    K --> L[Cabin Temperature]
    L --> C

    style A fill:#e1f5ff
    style B fill:#ffe1e1
    style L fill:#e1ffe1

Setpoint-Based Control Strategy

The ATC system establishes thermal targets based on occupant-selected setpoint temperatures (typically 18-32°C range). The control module calculates required discharge air temperature $T_{discharge}$ using:

$$T_{discharge} = T_{setpoint} - K_1(T_{cabin} - T_{setpoint}) - K_2\frac{dT_{cabin}}{dt} - K_3 Q_{solar}$$

Where $K_1$, $K_2$, and $K_3$ are calibrated gain coefficients for proportional, derivative, and solar compensation terms. This equation demonstrates feed-forward compensation (solar term) combined with feedback control (cabin temperature error and rate).

Temperature Feedback Loop Implementation

The primary feedback mechanism employs multiple temperature sensors with weighted averaging based on occupant proximity and airflow patterns.

Sensor Configuration and Weighting

The effective cabin temperature used for control is:

$$T_{cabin,eff} = \sum_{i=1}^{n} w_i T_i$$

Where $w_i$ represents the weighting factor for each sensor location, with $\sum w_i = 1$.

Discharge Air Temperature Control

Discharge air temperature regulation represents the inner control loop that executes faster than the cabin temperature loop. The target discharge temperature must satisfy:

$$\dot{m}{air}c_p(T{discharge} - T_{cabin}) \geq Q_{load}$$

For cooling mode, typical discharge temperatures range from 2°C to 18°C depending on cooling demand. The ECCM modulates temperature blend doors and evaporator temperature to achieve this target.

Evaporator Temperature Management

Evaporator surface temperature $T_{evap}$ is controlled to prevent frost formation while maximizing latent cooling. The minimum evaporator temperature is constrained by:

$$T_{evap,min} = T_{dew,air} - \Delta T_{approach}$$

Where $\Delta T_{approach}$ typically equals 2-4°C. Per SAE J2765, evaporator temperature should be maintained above 2°C to prevent ice formation under normal operation.

flowchart LR
    A[Target Discharge Temp] --> B{Calculate Required Cooling}
    B --> C[Evaporator Temp Setpoint]
    C --> D[Compressor Speed Adjust]
    C --> E[Expansion Valve Control]
    D --> F[Refrigerant Mass Flow]
    E --> F
    F --> G[Evaporator Capacity]
    G --> H[Air-Side Temp Drop]
    H --> I[Blend Door Position]
    I --> J[Final Discharge Temp]
    J --> K[Measure Actual Temp]
    K --> B

    style A fill:#ffebcc
    style J fill:#ccffcc

Variable Compressor Control

Modern ATC systems employ variable-displacement or variable-speed compressors to provide continuous capacity modulation rather than binary on/off cycling. The compressor capacity requirement is calculated from:

$$\dot{Q}{evap} = \dot{m}{ref}(h_{evap,out} - h_{evap,in})$$

The required refrigerant mass flow rate $\dot{m}_{ref}$ is achieved by adjusting compressor displacement (reciprocating) or rotational speed (scroll/electric). This enables:

• Precise capacity matching to thermal load
• Elimination of temperature oscillations from cycling
• Reduced power consumption at part-load conditions
• Improved humidity control through continuous operation

Compressor Command Calculation

The ECCM determines compressor command using a PI (Proportional-Integral) controller:

$$u_{comp}(t) = K_p e(t) + K_i \int_0^t e(\tau)d\tau$$

Where:

• $u_{comp}$ = Compressor speed or displacement command (%)
• $e(t)$ = $T_{evap,target} - T_{evap,actual}$
• $K_p$ = Proportional gain
• $K_i$ = Integral gain

Typical $K_p$ values range from 5-15 %/°C, while $K_i$ ranges from 0.5-2 %/(°C·s).

Blower Speed Modulation

Blower speed directly controls air-side mass flow rate, which governs both sensible cooling capacity and cabin air distribution. The relationship between blower voltage and airflow is nonlinear:

$$\dot{V}{air} = K{blower}V_{blower}^{1.8}$$

Where $K_{blower}$ is a system-specific constant determined by duct geometry and restriction.

The ECCM commands blower speed based on:

1. Temperature error magnitude: Higher error → higher airflow for faster response
2. Discharge air temperature: Lower discharge temperature → lower airflow to prevent overcooling sensation
3. Mode selection: Defrost requires maximum airflow regardless of temperature error
4. Acoustic limits: Speed limited to maintain noise below threshold (typically 50-55 dBA at ear level)

Blower Speed Algorithm

graph TD
    A[Calculate Temp Error] --> B{Error > 3°C?}
    B -->|Yes| C[High Speed Mode]
    B -->|No| D{Error > 1°C?}
    D -->|Yes| E[Medium Speed Mode]
    D -->|No| F{Error > 0.3°C?}
    F -->|Yes| G[Low Speed Mode]
    F -->|No| H[Minimum Speed]

    C --> I[Check Discharge Temp]
    E --> I
    G --> I
    H --> I

    I --> J{T_discharge < 8°C?}
    J -->|Yes| K[Reduce Speed 20%]
    J -->|No| L[Maintain Speed]
    K --> M[Final Command]
    L --> M

Thermal Comfort Algorithms

Advanced ATC systems incorporate Predicted Mean Vote (PMV) models based on ISO 7730 principles, adapted for automotive environments. The thermal comfort index accounts for:

$$PMV = f(T_{air}, T_{radiant}, v_{air}, RH, M_{metabolic}, I_{clothing})$$

For automotive applications, the metabolic rate $M$ is assumed constant (1.0-1.2 met for seated position), and clothing insulation $I_{clothing}$ is estimated seasonally (0.5-1.0 clo).

Multi-Zone Comfort Optimization

Dual-zone and multi-zone systems maintain independent setpoints for driver and passenger regions. The challenge involves managing thermal coupling between zones while minimizing inter-zone airflow mixing.

The thermal coupling coefficient $\alpha$ between zones is:

$$\frac{dT_{zone1}}{dt} = \frac{Q_{HVAC1} - Q_{load1}}{m_{zone1}c_p} - \alpha(T_{zone1} - T_{zone2})$$

Typical $\alpha$ values range from 0.05-0.15 s⁻¹ depending on cabin geometry and partition effectiveness.

Performance Metrics and Validation

Per SAE J2765 (Procedure for Measuring System COP of Mobile Air Conditioning Systems), ATC system performance is evaluated using:

The system Coefficient of Performance (COP) should exceed 1.8 under standard cooling conditions (35°C ambient, 50% RH) per SAE J2765 requirements.

Integration with Vehicle Systems

Modern ATC systems interface with vehicle networks (CAN, LIN, FlexRay) to optimize energy management. Integration includes:

• Engine load management (compressor clutch off during wide-open throttle)
• Battery state monitoring (reduced compressor load for hybrid/electric vehicles)
• GPS-based predictive control (tunnel detection, route-based solar prediction)
• Occupant detection (shutting off unoccupied zones)

This networked approach enables 10-15% energy savings compared to standalone ATC operation through coordinated optimization across vehicle systems.

Components

• ATC System Operation
• Electronic Climate Control
• Temperature Sensor Cabin
• Temperature Sensor Ambient
• Temperature Sensor Evaporator
• Temperature Sensor Sunload
• Humidity Sensor Cabin
• Control Module HVAC
• PID Control Algorithm
• Fuzzy Logic Control