A framework for real-time near-optimal train run-curve computation with dynamic travel time and speed limits

Xu, Jingyang; Nikovski, Daniel; Kimura, Sae

doi:10.1109/acc.2015.7170790

Cited by 3 publications

(3 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Optimal speed profiles have been researched for different vehicles and transportations including off-road vehicles [20], and vehicles moving on fixed routes, such as trains [21], buses [22], or race cars [23], [24]. [33][34][35][36][37][38][39][40][41][42][43][44][45][46][47][48][49][50][51][52]. The solutions of which can provide a vehicle speed profile that decreases the amount of energy consumed over the trip.…”

Section: Literature and Technology Reviewmentioning

confidence: 99%

Optimization of Energy-Efficient Speed Profile for Electrified Vehicles

Abbas

Kim

Siegel

et al. 2018

Volume 2: Control and Optimization of Connected and Automated Ground Vehicles; Dynamic Systems and Control Education; Dynamics

View full text Add to dashboard Cite

This paper presents a study of energy-efficient operation of vehicles with electrified powertrains leveraging route information, such as road grades, to adjust the speed trajectory. First, Pontryagin’s Maximum Principle (PMP) is applied to derive necessary conditions and to determine the possible operating modes. The analysis shows that only 5 modes are required to achieve minimum energy consumption; full propulsion, cruising, coasting, full regeneration, and full regeneration with conventional braking. The minimum energy consumption problem is reformulated and solved in the distance domain using Dynamic Programming to optimize speed profiles. A case study is shown for a light weight military robot including road grades. For this system, a tradeoff between energy consumption and trip time was found. The optimal cycle uses 20% less energy for the same trip duration, or could reduce the travel time by 14% with the same energy consumption compared to the baseline operation.

show abstract

Section: Literature and Technology Reviewmentioning

confidence: 99%

Optimization of Energy-Efficient Speed Profile for Electrified Vehicles

Abbas

Kim

Siegel

et al. 2018

Volume 2: Control and Optimization of Connected and Automated Ground Vehicles; Dynamic Systems and Control Education; Dynamics

View full text Add to dashboard Cite

show abstract

“…Eco-driving or energyefficient driving is the term given to the idea of determining the speed trajectory that minimizes the vehicle energy consumption under final time and distance constraints. This problem has been addressed as an optimal control problem (OCP) with related work done by researchers [3][4][5][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23], the solutions of which can provide a vehicle speed profile that decreases the amount of energy consumed over the trip.…”

Section: Introductionmentioning

confidence: 99%

“…In solving the trajectory optimization problem, numerical approaches such as genetic algorithm [7,14,16], ant colony algorithm [16], sequential quadratic programming [13], nonlinear programming [24], and dynamic programming (DP) [15][16][17]23,25] have been used for nonlinear characteristics, such as varying speed limits, resistive forces, and signal-phase timing. Among these, DP has been widely and extensively used because it can find a global optimum even for nonlinear systems with nonlinear constraints.…”

Section: Introductionmentioning

confidence: 99%

Synthesis of Pontryagin's Maximum Principle Analysis for Speed Profile Optimization of All-Electric Vehicles

Abbas

Kim

Siegel

et al. 2019

Journal of Dynamic Systems, Measurement, and Control

View full text Add to dashboard Cite

This paper presents a study of the energy-efficient operation of all-electric vehicles leveraging route information, such as road grade, to adjust the velocity trajectory. First, Pontryagin's maximum principle (PMP) is applied to derive necessary conditions and to determine the possible operating modes. The analysis shows that only five modes are required to achieve minimum energy consumption: full propulsion, cruising, coasting, full regeneration, and full regeneration with conventional braking. Then, the minimum energy consumption problem is reformulated and solved in the distance domain using dynamic programming to find the optimal speed profiles. Various simulation results are shown for a lightweight autonomous military vehicle. The sensitivity of energy consumption to regenerative-braking power limits and trip time is investigated. These studies provide important information that can be used in designing component size and scheduling operation to achieve the desired vehicle range.

show abstract