Control Strategies for Dual-Clutch Transmission Systems

Dual-clutch transmission (DCT) systems employ two independently actuated clutches to alternate torque transfer between odd and even gear sets, enabling rapid gear changes without interrupting engine power delivery. Central to DCT performance is the control of clutch engagement and disengagement phases—commonly divided into torque phase and inertia phase—to achieve smooth torque handover, minimise shift jerk and optimise energy efficiency. Early strategies relied on fixed-band proportional–integral–derivative (PID) controllers to regulate clutch pressure, but these often struggled with varying temperatures, wear and manufacturing tolerances. More recent approaches integrate model-based predictive control, adaptive fuzzy logic and sliding-mode variable structure control to anticipate driver intent, accommodate system nonlinearities and compensate for disturbances in real time. Optimal control techniques, including linear–quadratic regulators and multi-objective genetic algorithms, have been applied to balance trade-offs between shift duration, comfort and mechanical losses. Advances in sensor technology and data-driven identification further support predictive adaptation of control laws. Taken together, these developments have broadened the application of DCTs beyond passenger cars to hybrid electric vehicles, heavy-duty mining trucks, agricultural tractors and construction machinery, underscoring the global significance of robust, high-performance clutch control in modern power-train design.

Research from Nature Portfolio

No recent Nature Portfolio content available.

Control Strategies for Dual-Clutch Transmission Systems publication trend

The graph below shows the total number of articles in control strategies for dual-clutch transmission systems across all publications each year (not limited to Nature Index journals).

Technical terms

Dual-clutch transmission (DCT): A gearbox architecture with two clutches that alternately engage odd and even gears for uninterrupted torque flow.

Torque phase: The interval during which a disengaged clutch absorbs torque from the engine before the next gear is engaged.

Inertia phase: The period when both clutches slip to match rotational speeds of input and output shafts for seamless gear change.

Fuzzy logic control: An adaptive rule-based methodology that handles system uncertainty by mapping linguistic rules to control actions.

Model predictive control (MPC): A strategy that uses an internal dynamic model to forecast future behaviour and optimises control inputs over a finite horizon.

Sliding-mode control: A robust variable-structure approach that forces system trajectories to “slide” along a predetermined surface for disturbance rejection.

References

1. Optimizing Automatic Transmission Double-Transition Shift Process Based on Multi-Objective Genetic Algorithm. Applied Sciences (2020).
2. Fuzzy Determination of Target Shifting Time and Torque Control of Shifting Phase for Dry Dual Clutch Transmission. Mathematical Problems in Engineering (2014).
3. Sliding Mode Variable Structure Control and Real‐Time Optimization of Dry Dual Clutch Transmission during the Vehicle’s Launch. Mathematical Problems in Engineering (2014).
4. Adaptive Starting Control Strategy for Hybrid Electric Vehicles Equipped with a Wet Dual-Clutch Transmission. Actuators (2023).
5. A Novel Algorithm for Hydrostatic-Mechanical Mobile Machines with a Dual-Clutch Transmission. Energies (2022).