Search Results

Transmission system models require a high level of fidelity and details in order to capture the transient behaviors in drivability and fuel economy simulations. Due to model fidelity, manufacturing tolerances, frictional losses and other noise sources, parametrization and tuning of a large number of parameters in the plant model is very challenging and time consuming. In this paper, we used particle swarm optimization as the key algorithm to fast correlate the open-loop performance of an automatic transmission system plant model to vehicle launch and coast down test data using vehicle control inputs. During normal operations, the model correlated well with test data. For error states, due to the lack of model fidelity, the model cannot reproduce the same error state quantitatively, but provided a valuable methodology for qualitatively identifying error states at the early stages.

A direct trajectory optimization approach is developed to assess the capability of a GTDI-DCT Powertrain, with a Gasoline Turbocharged Direct Injection (GTDI) engine and Dual Clutch Transmission (DCT), to satisfy stringent drivability requirements during launch. The optimization is performed directly on a high fidelity black box powertrain model for which a single simulation of a launch event takes about 8 minutes. To address this challenging problem, an efficient parameterization of the control trajectory using Gaussian kernel functions and a Mesh Adaptive Direct Search optimizer are exploited. The results and observations are reported for the case of clutch torque optimization for launch at normal conditions, at high altitude conditions and at non-zero grade conditions. The results and observations are also presented for the case of simultaneous optimization of multiple actuator trajectories at normal conditions.

This paper proposes an approach that uses the road preview data to optimize a shift schedule for a vehicle equipped with an automatic transmission. The road preview is inferred here from the so-called electronic horizon of a digital map that includes road attributes such as road grade, curvature, segment speed limit, functional class, etc. The optimized shift schedule selects the gear ratio whose optimization is conducted through applying a hybrid model predictive control method to the powertrain system, which is modelled as the multiple plants associated with multiple gears together with engine models. The goal of this optimization of shift schedule includes improving real world fuel economy and drivability. The real-world fuel economy gains using the proposed approach are achieved through optimizing gear ratio w.r.t. the road grade variations of the road ahead.