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Zhang, Chen (ORCID:0000000181901887)

Publications and source records attributed to Zhang, Chen (ORCID:0000000181901887).

Decision Tree Regression to Identify Representative Road Sections for Evaluating Performance of Connected and Automated Class 8 Tractors

Currently, connected and autonomous vehicle (CAV) technology is being developed for Class 8 tractor trucks aimed at improved safety and fuel economy and reduced CO2 emissions. Despite extensive efforts conducted across the world, the reported efficiency gains were varied from different research groups, raising concerns about the fidelity of models, the performance of control, and the effectiveness of the experimental validation. One root cause for this variation stems from the fact that the efficiency gain obtained from the CAV is sensitive to real-world conditions, including surrounding traffic and road grade. This study presents an approach aimed at identifying representative public road sections and facilitating CAV research from this perspective. By employing the decision tree regression (DTR) method to the Fleet DNA database, the most representative road sections can be identified. High-level metrics and detailed information of the derived road sections are also illustrated and discussed, which demonstrate their representativeness and the effectiveness of the approach. Meanwhile, the capability of this approach can be easily extended by integrating specific constraints into the DTR algorithm. As an example, a specific representative road section with an aggressive road grade profile was also provided via this approach.

27 ARPA - Advanced Research Projects Agency-Energy↗

Impact of Lateral Alignment for Cooling Airflow during Heavy-Truck Platooning

A truck platooning system was tested using two heavy-duty tractor-trailer trucks on a closed test track to investigate the thermal control/heat rejection system sensitivity to intentional lateral offsets over a range of intervehicle spacings. Previous studies have shown the following vehicle can experience elevated temperatures and reduced airflow through the cooling package as a result of close-formation platooning. Four anemometers positioned across the grille of the following trucks as well as aligned and multiple offset positions are used to evaluate the sensitivity of the impact. Straight sections of the track are isolated for the most accurate airflow impact measurements and to be most representative of on-highway driving. An intentional lateral offset in truck platooning is considered as a controls approach to mitigate reduced cooling efficacy at close following scenarios where the highest platoon savings are achieved. The truck platooning system was tested at four gap distances from 9 to 23 meters and the following truck was either aligned with the lead or offset with a 25% width (0.65 m) or 50% width (1.3 m) lateral distance. The experimental results clearly show that offset driving is effective at bringing cooling airflow from 56% with an aligned platoon back up to 75%-80% with minimal impact to fuel savings. In addition, the offset driving can also reduce the trailing truck’s engine coolant temperature by 2°C and the corresponding underhood temperature rise by 10°C. The test outcomes indicate a plausible controls strategy to mitigate reduced cooling flow during hot-weather truck platooning while still enabling the highest-energy-saving, close-following scenarios.

27 ARPA - Advanced Research Projects Agency-Energy↗

Advancing Platooning with ADAS Control Integration and Assessment Test Results

The application of cooperative adaptive cruise control (CACC) to heavy-duty trucks known as truck platooning has shown fuel economy improvements over test track ideal driving conditions. However, there are limited test data available to assess the performance of CACC under real-world driving conditions. As part of the Cummins-led U.S. Department of Energy Funding Opportunity Announcement award project, truck platooning with CACC has been tested under real-world driving conditions and the results are presented in this paper. First, real-world driving conditions are characterized with the National Renewable Energy Laboratory’s Fleet DNA database to define the test factors. The key test factors impacting long-haul truck fuel economy were identified as terrain and highway traffic with and without advanced driver-assistance systems (ADAS). Track and on-highway testing guided by SAE J1321 procedures were conducted to assess truck platooning operation under the characterized real-world driving conditions. On-highway testing is done on a route in Indiana representing operation of long-haul Class 8 trucks in the United States. The road includes low-, medium-, and high-grade segments. The highway test results of a two-truck platooning configuration indicate considerable fuel-saving reduction comparing to the test track data collected under ideal driving conditions. The test data indicate that platooning could lead to increases in fuel consumption during traffic or high-grade portions of the route, causing reduction of the overall fuel saving on the road comparing to test track results. However, integration of ADAS features on the lead truck during on-road tests leads to significant improvement of fuel saving for both trucks in CACC operation.

ADAS↗

Impact to Cooling Airflow from Truck Platooning: Preprint

We investigate tradeoffs between the airflow strategies related to engine cooling and the aerodynamic-enabled fuel savings created by platooning. By analyzing air temperatures, engine temperatures and cooling air flow at different platoon distances, we show the thermal impact to the engine from truck platooning. Previously, we collected wind and thermal data for numerous heavy-duty truck platoon configurations (gaps ranging from 4 to 87 meters) and reported the significant fuel savings enabled by these configurations. The fuel consumption for all trucks in the platoon were measured using the SAE J1321 gravimetric procedure as well as calibrated J1939 instantaneous fuel rate while travelling at 65 mph and loaded to a gross weight of 65,000 lb. Using thermocouples mounted 1 m ahead of each truck, anemometers at the grill and a grid of under-hood thermocouples as well as J1939 reported engine temperatures, we analyze the impact to critical operating temperatures from different platoon configurations. Results show significant changes in the engine and under-hood air temperatures that correlate with vehicle gap distance and platoon position.

47 OTHER INSTRUMENTATION↗