Center for Environmental Research and Technology

Summary

Transit buses play an important role in today’s surface transportation system, providing mobility to millions of passengers. The majority of transit buses operate on surface streets where there are frequent stops and idling events associated with bus stops, traffic lights, and recurrent congestion. As such, these buses are excellent candidates for electric hybridization; indeed, a variety of hybrid electric buses are now being deployed across the United States. However, a typical hybrid electric bus is not very well optimized in terms of its energy efficiency, often relying on simple charge sustaining strategies.
As part of the ARPA-E NEXTCAR program, the Connected Eco-Bus team has developed and applied connected and automated vehicle (CAV) technology to achieve transformational energy efficiency improvements for transit buses well in excess of 20%. This was accomplished by designing, developing, and applying an innovative vehicle-powertrain eco-operation system through co-optimization of vehicle dynamics and powertrain controls.
The team developed a prototype Connected Eco-Bus, which is a power-split plug-in hybrid electric bus with a natural gas internal combustion engine and electric motors, coupled with 38 kWh of lithium-ion batteries. The Connected Eco-Bus is able to communicate with the roadway infrastructure (traffic Signal Phase and Timing or SPaT, downstream traffic volume) and sense local traffic (e.g., forward radar) to optimally plan vehicle dynamics in terms of a target velocity trajectory. Three key innovative velocity trajectory planning modules have been developed:

• Eco-Approach and Departure at Signalized Intersections - Determines an energy-efficient speed profile based on SPaT information from signalized intersections;
• Eco-Stop and Launch - Determines energy-efficient speed profile for decelerating to and accelerating from bus stops and stop signs;
• Eco-Cruise - Determines cruising speed profile based on look-ahead traffic and terrain conditions;
• In addition, two key innovative powertrain modules have been developed:
• Efficiency Based Powertrain Controls - Optimizes both the engine and motor/generator operation by managing transmission and battery state-of-charge;
• Intelligent Energy Management - Optimizes the power split between the internal combustion engine and electric motors for the vehicle speed and power demand profiles;

These technologies have been integrated, implemented on the Connected Eco-Bus, and extensively tested both in simulation and in the real-world. Another innovative accomplishment of this project is a new hardware-in-the-loop development and testing approach called Dyno-in-the-Loop (DiL) evaluation [1]. This approach integrates a test vehicle, a chassis dynamometer, and high-fidelity traffic simulation tools, in order to achieve a balance between model accuracy and scalability for environmental analysis.
Using these techniques, the Connected Eco-Bus was evaluated on a typical bus route in Riverside California. The operation of the bus was evaluated under a number of conditions, including different levels of traffic (i.e., none, light, moderate, heavy, and very heavy traffic conditions) and different levels of connected vehicle penetration (i.e., 0% and 20% penetration rates). The original plug-in hybrid electric bus platform (with no improvements to the vehicle dynamics and powertrain) was first tested to serve as a baseline for subsequent comparisons. Various tests were conducted, evaluating separately the integrated vehicle dynamics speed trajectory planning (VD) and the efficiency-based powertrain controls (PT), as well as the combined VD and PT. The tests were conducted both in simulation and using the Dyno-in-the-Loop methodology.
The final results of the bus performance using a combined VD and PT strategy on the target bus route was an energy efficiency improvement ranging from 19.4% to 32.4%, depending on congestion conditions and penetration rate of connected vehicles. This efficiency improvement met our targeted goal of exceeding 20%.
The relative cost of including real-time roadway infrastructure information as part of a co-optimized on-board energy strategy is low, resulting in significant energy savings. This connected co-optimization can also be applied to the heavy-duty truck sector, which could potentially increase energy savings and reduce emissions from that sector. More information..